[08-2020] python-data-science-machine-learning-bootcamp

Creation Time	Sept. 14, 2023, 3:59 p.m.
Last Access Time	Dec. 17, 2024, 11:09 a.m.
File Size	23.2 GB
Keywords	08-2020 python-data-science-machine-learning-bootcamp
Total Requests	172
Total Files	452
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04 Introduction to Optimisation and the Gradient Descent Algorithm/036 [Python] - Loops and the Gradient Descent Algorithm.mp4 449.2 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 446.8 MB
12 Serving a Tensorflow Model through a Website/198 Introduction to OpenCV.mp4 432.3 MB
12 Serving a Tensorflow Model through a Website/200 Calculating the Centre of Mass and Shifting the Image.mp4 405.9 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/169 Model Evaluation and the Confusion Matrix.mp4 366.4 MB
03 Python Programming for Data Science and Machine Learning/021 [Python] - Module Imports.mp4 349.5 MB
11 Use Tensorflow to Classify Handwritten Digits/183 Different Model Architectures_ Experimenting with Dropout.mp4 335.8 MB
05 Predict House Prices with Multivariable Linear Regression/068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 334.5 MB
12 Serving a Tensorflow Model through a Website/193 Loading a Tensorflow.js Model and Starting your own Server.mp4 321.3 MB
12 Serving a Tensorflow Model through a Website/195 Styling an HTML Canvas.mp4 312.4 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 302.3 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/167 Use the Model to Make Predictions.mp4 300.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/040 How to Create 3-Dimensional Charts.mp4 294.3 MB
12 Serving a Tensorflow Model through a Website/196 Drawing on an HTML Canvas.mp4 291.0 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.mp4 287.1 MB
12 Serving a Tensorflow Model through a Website/199 Resizing and Adding Padding to Images.mp4 286.3 MB
12 Serving a Tensorflow Model through a Website/202 Adding the Game Logic.mp4 286.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/039 Understanding the Learning Rate.mp4 280.5 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/141 Visualising the Decision Boundary.mp4 277.3 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/146 A Naive Bayes Implementation using SciKit Learn.mp4 270.5 MB
03 Python Programming for Data Science and Machine Learning/026 How to Make Sense of Python Documentation for Data Visualisation.mp4 265.0 MB
03 Python Programming for Data Science and Machine Learning/027 Working with Python Objects to Analyse Data.mp4 258.8 MB
12 Serving a Tensorflow Model through a Website/192 HTML and CSS Styling.mp4 244.6 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/150 Layers, Feature Generation and Learning.mp4 237.2 MB
03 Python Programming for Data Science and Machine Learning/025 [Python] - Objects - Understanding Attributes and Methods.mp4 234.5 MB
05 Predict House Prices with Multivariable Linear Regression/077 Model Simplification & Baysian Information Criterion.mp4 229.5 MB
05 Predict House Prices with Multivariable Linear Regression/081 Making Predictions (Part 1)_ MSE & R-Squared.mp4 217.8 MB
05 Predict House Prices with Multivariable Linear Regression/058 Clean and Explore the Data (Part 2)_ Find Missing Values.mp4 207.9 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/043 [Python] - Loops and Performance Considerations.mp4 205.6 MB
11 Use Tensorflow to Classify Handwritten Digits/177 Creating Tensors and Setting up the Neural Network Architecture.mp4 205.1 MB
03 Python Programming for Data Science and Machine Learning/020 [Python & Pandas] - Dataframes and Series.mp4 203.6 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/129 Create a Full Matrix.mp4 200.5 MB
05 Predict House Prices with Multivariable Linear Regression/083 Build a Valuation Tool (Part 1)_ Working with Pandas Series & Numpy ndarrays.mp4 198.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/098 [Python] - Generator Functions & the yield Keyword.mp4 197.7 MB
05 Predict House Prices with Multivariable Linear Regression/061 Working with Index Data, Pandas Series, and Dummy Variables.mp4 195.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/164 Interacting with the Operating System and the Python Try-Catch Block.mp4 193.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/041 Understanding Partial Derivatives and How to use SymPy.mp4 193.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/100 Cleaning Data (Part 1)_ Check for Empty Emails & Null Entries.mp4 191.9 MB
12 Serving a Tensorflow Model through a Website/188 Saving Tensorflow Models.mp4 191.8 MB
05 Predict House Prices with Multivariable Linear Regression/065 Visualising Correlations with a Heatmap.mp4 191.5 MB
03 Python Programming for Data Science and Machine Learning/023 [Python] - Functions - Part 2_ Arguments & Parameters.mp4 189.7 MB
02 Predict Movie Box Office Revenue with Linear Regression/008 Explore & Visualise the Data with Python.mp4 188.8 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/089 Gathering Email Data and Working with Archives & Text Editors.mp4 186.9 MB
11 Use Tensorflow to Classify Handwritten Digits/180 Tensorboard Summaries and the Filewriter.mp4 186.5 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/115 Styling the Word Cloud with a Mask.mp4 184.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/117 Styling Word Clouds with Custom Fonts.mp4 184.2 MB
12 Serving a Tensorflow Model through a Website/201 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 181.8 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/154 Making Predictions using InceptionResNet.mp4 181.2 MB
05 Predict House Prices with Multivariable Linear Regression/080 Residual Analysis (Part 2)_ Graphing and Comparing Regression Residuals.mp4 178.2 MB
12 Serving a Tensorflow Model through a Website/190 Converting a Model to Tensorflow.js.mp4 171.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/093 Joint & Conditional Probability.mp4 169.3 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/044 Reshaping and Slicing N-Dimensional Arrays.mp4 168.3 MB
05 Predict House Prices with Multivariable Linear Regression/085 Build a Valuation Tool (Part 3)_ Docstrings & Creating your own Python Module.mp4 167.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/108 Removing HTML tags with BeautifulSoup.mp4 167.5 MB
11 Use Tensorflow to Classify Handwritten Digits/181 Understanding the Tensorflow Graph_ Nodes and Edges.mp4 167.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/096 Reading Files (Part 2)_ Stream Objects and Email Structure.mp4 167.3 MB
05 Predict House Prices with Multivariable Linear Regression/076 Understanding VIF & Testing for Multicollinearity.mp4 164.6 MB
11 Use Tensorflow to Classify Handwritten Digits/184 Prediction and Model Evaluation.mp4 162.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.mp4 160.5 MB
05 Predict House Prices with Multivariable Linear Regression/084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 159.9 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/155 Coding Challenge Solution_ Using other Keras Models.mp4 155.0 MB
05 Predict House Prices with Multivariable Linear Regression/064 Calculating Correlations and the Problem posed by Multicollinearity.mp4 154.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/114 Creating your First Word Cloud.mp4 152.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/161 Exploring the CIFAR Data.mp4 151.1 MB
05 Predict House Prices with Multivariable Linear Regression/066 Techniques to Style Scatter Plots.mp4 150.0 MB
05 Predict House Prices with Multivariable Linear Regression/079 Residual Analysis (Part 1)_ Predicted vs Actual Values.mp4 146.5 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/151 Costs and Disadvantages of Neural Networks.mp4 145.9 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 145.6 MB
12 Serving a Tensorflow Model through a Website/189 Loading a SavedModel.mp4 144.9 MB
05 Predict House Prices with Multivariable Linear Regression/074 Improving the Model by Transforming the Data.mp4 142.5 MB
02 Predict Movie Box Office Revenue with Linear Regression/010 Analyse and Evaluate the Results.mp4 142.2 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 139.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/106 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 138.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/125 Checkpoint_ Understanding the Data.mp4 134.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/103 Data Visualisation (Part 1)_ Pie Charts.mp4 131.1 MB
03 Python Programming for Data Science and Machine Learning/028 [Python] - Tips, Code Style and Naming Conventions.mp4 130.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/051 Running Gradient Descent with a MSE Cost Function.mp4 129.8 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 Preprocessing Image Data and How RGB Works.mp4 129.6 MB
11 Use Tensorflow to Classify Handwritten Digits/179 TensorFlow Sessions and Batching Data.mp4 128.9 MB
12 Serving a Tensorflow Model through a Website/191 Introducing the Website Project and Tooling.mp4 125.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/118 Create the Vocabulary for the Spam Classifier.mp4 124.0 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/121 Sparse Matrix (Part 1)_ Split the Training and Testing Data.mp4 119.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/042 Implementing Batch Gradient Descent with SymPy.mp4 117.5 MB
05 Predict House Prices with Multivariable Linear Regression/082 Making Predictions (Part 2)_ Standard Deviation, RMSE, and Prediction Intervals.mp4 116.5 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/130 Count the Tokens to Train the Naive Bayes Model.mp4 111.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.mp4 110.8 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/035 Understanding the Power Rule & Creating Charts with Subplots.mp4 104.5 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.mp4 103.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/047 Transposing and Reshaping Arrays.mp4 101.7 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/112 [Python] - Logical Operators to Create Subsets and Indices.mp4 101.3 MB
05 Predict House Prices with Multivariable Linear Regression/057 Clean and Explore the Data (Part 1)_ Understand the Nature of the Dataset.mp4 99.4 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 99.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/111 Advanced Subsetting on DataFrames_ the apply() Function.mp4 97.9 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/048 Implementing a MSE Cost Function.mp4 97.5 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/094 Bayes Theorem.mp4 94.5 MB
03 Python Programming for Data Science and Machine Learning/024 [Python] - Functions - Part 3_ Results & Return Values.mp4 94.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/116 Solving the Hamlet Challenge.mp4 92.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/113 Word Clouds & How to install Additional Python Packages.mp4 92.4 MB
05 Predict House Prices with Multivariable Linear Regression/056 Gathering the Boston House Price Data.mp4 91.0 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/138 Joint Conditional Probablity (Part 2)_ Priors.mp4 90.7 MB
05 Predict House Prices with Multivariable Linear Regression/075 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 89.1 MB
11 Use Tensorflow to Classify Handwritten Digits/182 Name Scoping and Image Visualisation in Tensorboard.mp4 88.7 MB
11 Use Tensorflow to Classify Handwritten Digits/175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.mp4 88.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/052 Visualising the Optimisation on a 3D Surface.mp4 88.2 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/045 Concatenating Numpy Arrays.mp4 85.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/101 Cleaning Data (Part 2)_ Working with a DataFrame Index.mp4 84.9 MB
11 Use Tensorflow to Classify Handwritten Digits/178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 84.8 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/137 Joint Conditional Probability (Part 1)_ Dot Product.mp4 84.7 MB
03 Python Programming for Data Science and Machine Learning/018 [Python] - Variables and Types.mp4 84.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/107 Word Stemming & Removing Punctuation.mp4 83.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/049 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 83.4 MB
05 Predict House Prices with Multivariable Linear Regression/070 How to Shuffle and Split Training & Testing Data.mp4 83.3 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/168 Model Evaluation and the Confusion Matrix.mp4 81.8 MB
03 Python Programming for Data Science and Machine Learning/015 Mac Users - Install Anaconda.mp4 81.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/102 Saving a JSON File with Pandas.mp4 81.3 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/034 LaTeX Markdown and Generating Data with Numpy.mp4 77.2 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/033 Introduction to Cost Functions.mp4 76.9 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/120 Coding Challenge_ Find the Longest Email.mp4 76.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/046 Introduction to the Mean Squared Error (MSE).mp4 75.2 MB
11 Use Tensorflow to Classify Handwritten Digits/173 Getting the Data and Loading it into Numpy Arrays.mp4 75.1 MB
05 Predict House Prices with Multivariable Linear Regression/071 Running a Multivariable Regression.mp4 74.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/104 Data Visualisation (Part 2)_ Donut Charts.mp4 73.4 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/153 Importing Keras Models and the Tensorflow Graph.mp4 73.4 MB
05 Predict House Prices with Multivariable Linear Regression/062 Understanding Descriptive Statistics_ the Mean vs the Median.mp4 72.5 MB
05 Predict House Prices with Multivariable Linear Regression/059 Visualising Data (Part 1)_ Historams, Distributions & Outliers.mp4 71.9 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/142 False Positive vs False Negatives.mp4 71.6 MB
01 Introduction to the Course/002 What is Data Science_.mp4 71.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/095 Reading Files (Part 1)_ Absolute Paths and Relative Paths.mp4 71.1 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/132 Calculate the Token Probabilities and Save the Trained Model.mp4 70.5 MB
11 Use Tensorflow to Classify Handwritten Digits/176 What is a Tensor_.mp4 69.7 MB
02 Predict Movie Box Office Revenue with Linear Regression/007 Gather & Clean the Data.mp4 69.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/050 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 68.9 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/139 Making Predictions_ Comparing Joint Probabilities.mp4 68.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/099 Create a Pandas DataFrame of Email Bodies.mp4 67.9 MB
03 Python Programming for Data Science and Machine Learning/016 Does LSD Make You Better at Maths_.mp4 66.9 MB
05 Predict House Prices with Multivariable Linear Regression/060 Visualising Data (Part 2)_ Seaborn and Probability Density Functions.mp4 66.2 MB
12 Serving a Tensorflow Model through a Website/187 What you'll make.mp4 64.4 MB
05 Predict House Prices with Multivariable Linear Regression/069 Understanding Multivariable Regression.mp4 61.6 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/144 The Precision Metric.mp4 61.5 MB
03 Python Programming for Data Science and Machine Learning/019 [Python] - Lists and Arrays.mp4 60.9 MB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 60.5 MB
12 Serving a Tensorflow Model through a Website/203 Publish and Share your Website!.mp4 59.5 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/159 Installing Tensorflow and Keras for Jupyter.mp4 58.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/105 Introduction to Natural Language Processing (NLP).mp4 58.2 MB
03 Python Programming for Data Science and Machine Learning/014 Windows Users - Install Anaconda.mp4 58.2 MB
05 Predict House Prices with Multivariable Linear Regression/055 Defining the Problem.mp4 57.8 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/088 How to Translate a Business Problem into a Machine Learning Problem.mp4 57.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/091 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 57.2 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/097 Extracting the Text in the Email Body.mp4 55.2 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/133 Coding Challenge_ Prepare the Test Data.mp4 53.7 MB
03 Python Programming for Data Science and Machine Learning/022 [Python] - Functions - Part 1_ Defining and Calling Functions.mp4 47.0 MB
05 Predict House Prices with Multivariable Linear Regression/078 How to Analyse and Plot Regression Residuals.mp4 46.6 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/140 The Accuracy Metric.mp4 46.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/109 Creating a Function for Text Processing.mp4 44.8 MB
12 Serving a Tensorflow Model through a Website/197 Data Pre-Processing for Tensorflow.js.mp4 42.4 MB
12 Serving a Tensorflow Model through a Website/194 Adding a Favicon.mp4 42.1 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/131 Sum the Tokens across the Spam and Ham Subsets.mp4 39.6 MB
02 Predict Movie Box Office Revenue with Linear Regression/006 Introduction to Linear Regression & Specifying the Problem.mp4 38.8 MB
05 Predict House Prices with Multivariable Linear Regression/072 How to Calculate the Model Fit with R-Squared.mp4 38.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/158 Solving a Business Problem with Image Classification.mp4 37.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/124 Coding Challenge Solution_ Preparing the Test Data.mp4 37.5 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 Set up the Testing Notebook.mp4 36.9 MB
11 Use Tensorflow to Classify Handwritten Digits/174 Data Exploration and Understanding the Structure of the Input Data.mp4 35.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/160 Gathering the CIFAR 10 Dataset.mp4 35.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/090 How to Add the Lesson Resources to the Project.mp4 35.1 MB
01 Introduction to the Course/001 What is Machine Learning_.mp4 32.4 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/143 The Recall Metric.mp4 32.0 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/145 The F-score or F1 Metric.mp4 28.7 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/031 What's Coming Up_.mp4 24.6 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 SpamData.zip 22.8 MB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 SpamData.zip 22.3 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/089 SpamData.zip 21.3 MB
05 Predict House Prices with Multivariable Linear Regression/063 Introduction to Correlation_ Understanding Strength & Direction.mp4 20.4 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/119 Coding Challenge_ Check for Membership in a Collection.mp4 19.9 MB
02 Predict Movie Box Office Revenue with Linear Regression/009 The Intuition behind the Linear Regression Model.mp4 19.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/032 How a Machine Learns.mp4 16.6 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/092 Basic Probability.mp4 15.5 MB
11 Use Tensorflow to Classify Handwritten Digits/173 MNIST.zip 14.8 MB
05 Predict House Prices with Multivariable Linear Regression/073 Introduction to Model Evaluation.mp4 12.0 MB
11 Use Tensorflow to Classify Handwritten Digits/172 What's coming up_.mp4 7.6 MB
12 Serving a Tensorflow Model through a Website/202 math-garden-stub-complete.zip 4.1 MB
12 Serving a Tensorflow Model through a Website/198 math-garden-stub-12.12-checkpoint.zip 4.1 MB
05 Predict House Prices with Multivariable Linear Regression/086 04-Multivariable-Regression.ipynb.zip 3.5 MB
12 Serving a Tensorflow Model through a Website/189 MNIST-Model-Load-Files.zip 2.8 MB
03 Python Programming for Data Science and Machine Learning/017 12-Rules-to-Learn-to-Code.pdf 2.2 MB
12 Serving a Tensorflow Model through a Website/190 TFJS.zip 1.5 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/053 03-Gradient-Descent.ipynb.zip 1.1 MB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/126 06-Bayes-Classifier-Pre-Processing.ipynb.zip 978.0 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/156 09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 571.8 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 TF-Keras-Classification-Images.zip 501.1 KB
02 Predict Movie Box Office Revenue with Linear Regression/007 cost-revenue-dirty.csv 374.7 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/147 07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 243.1 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/170 10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 120.1 KB
01 Introduction to the Course/003 ML-Data-Science-Syllabus.pdf 104.0 KB
02 Predict Movie Box Office Revenue with Linear Regression/008 cost-revenue-clean.csv 90.8 KB
02 Predict Movie Box Office Revenue with Linear Regression/011 01-Linear-Regression-complete.ipynb.zip 75.3 KB
12 Serving a Tensorflow Model through a Website/191 math-garden-stub.zip 44.0 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/036 [Python] - Loops and the Gradient Descent Algorithm.en_US.srt 40.2 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).en_US.srt 39.6 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/169 Model Evaluation and the Confusion Matrix.en_US.srt 38.9 KB
12 Serving a Tensorflow Model through a Website/195 Styling an HTML Canvas.en_US.srt 38.0 KB
02 Predict Movie Box Office Revenue with Linear Regression/009 01-Linear-Regression-checkpoint.ipynb.zip 37.6 KB
12 Serving a Tensorflow Model through a Website/198 Introduction to OpenCV.en_US.srt 36.9 KB
12 Serving a Tensorflow Model through a Website/202 Adding the Game Logic.en_US.srt 36.6 KB
12 Serving a Tensorflow Model through a Website/192 HTML and CSS Styling.en_US.srt 36.5 KB
03 Python Programming for Data Science and Machine Learning/029 02-Python-Intro.ipynb.zip 36.4 KB
12 Serving a Tensorflow Model through a Website/196 Drawing on an HTML Canvas.en_US.srt 36.3 KB
12 Serving a Tensorflow Model through a Website/193 Loading a Tensorflow.js Model and Starting your own Server.en_US.srt 35.8 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/039 Understanding the Learning Rate.en_US.srt 34.7 KB
12 Serving a Tensorflow Model through a Website/200 Calculating the Centre of Mass and Shifting the Image.en_US.srt 34.1 KB
03 Python Programming for Data Science and Machine Learning/021 [Python] - Module Imports.en_US.srt 33.4 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/146 A Naive Bayes Implementation using SciKit Learn.en_US.srt 32.4 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/141 Visualising the Decision Boundary.en_US.srt 32.2 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/167 Use the Model to Make Predictions.en_US.srt 31.8 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).en_US.srt 30.9 KB
11 Use Tensorflow to Classify Handwritten Digits/183 Different Model Architectures_ Experimenting with Dropout.en_US.srt 29.0 KB
02 Predict Movie Box Office Revenue with Linear Regression/008 Explore & Visualise the Data with Python.en_US.srt 28.6 KB
11 Use Tensorflow to Classify Handwritten Digits/177 Creating Tensors and Setting up the Neural Network Architecture.en_US.srt 28.0 KB
03 Python Programming for Data Science and Machine Learning/025 [Python] - Objects - Understanding Attributes and Methods.en_US.srt 27.5 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.en_US.srt 27.2 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/150 Layers, Feature Generation and Learning.en_US.srt 26.8 KB
05 Predict House Prices with Multivariable Linear Regression/068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.en_US.srt 26.5 KB
05 Predict House Prices with Multivariable Linear Regression/085 Build a Valuation Tool (Part 3)_ Docstrings & Creating your own Python Module.en_US.srt 26.1 KB
03 Python Programming for Data Science and Machine Learning/020 [Python & Pandas] - Dataframes and Series.en_US.srt 25.9 KB
12 Serving a Tensorflow Model through a Website/199 Resizing and Adding Padding to Images.en_US.srt 25.8 KB
11 Use Tensorflow to Classify Handwritten Digits/182 Name Scoping and Image Visualisation in Tensorboard.en_US.srt 25.3 KB
12 Serving a Tensorflow Model through a Website/189 Loading a SavedModel.en_US.srt 25.2 KB
03 Python Programming for Data Science and Machine Learning/027 Working with Python Objects to Analyse Data.en_US.srt 25.1 KB
03 Python Programming for Data Science and Machine Learning/026 How to Make Sense of Python Documentation for Data Visualisation.en_US.srt 24.5 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/040 How to Create 3-Dimensional Charts.en_US.srt 24.0 KB
05 Predict House Prices with Multivariable Linear Regression/076 Understanding VIF & Testing for Multicollinearity.en_US.srt 23.7 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/164 Interacting with the Operating System and the Python Try-Catch Block.en_US.srt 22.8 KB
05 Predict House Prices with Multivariable Linear Regression/065 Visualising Correlations with a Heatmap.en_US.srt 22.5 KB
11 Use Tensorflow to Classify Handwritten Digits/180 Tensorboard Summaries and the Filewriter.en_US.srt 22.4 KB
05 Predict House Prices with Multivariable Linear Regression/081 Making Predictions (Part 1)_ MSE & R-Squared.en_US.srt 21.8 KB
05 Predict House Prices with Multivariable Linear Regression/077 Model Simplification & Baysian Information Criterion.en_US.srt 21.4 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/044 Reshaping and Slicing N-Dimensional Arrays.en_US.srt 21.2 KB
05 Predict House Prices with Multivariable Linear Regression/080 Residual Analysis (Part 2)_ Graphing and Comparing Regression Residuals.en_US.srt 21.0 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/129 Create a Full Matrix.en_US.srt 20.9 KB
02 Predict Movie Box Office Revenue with Linear Regression/010 Analyse and Evaluate the Results.en_US.srt 20.8 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/098 [Python] - Generator Functions & the yield Keyword.en_US.srt 20.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/122 Sparse Matrix (Part 2)_ Data Munging with Nested Loops.en_US.srt 20.6 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/051 Running Gradient Descent with a MSE Cost Function.en_US.srt 20.5 KB
12 Serving a Tensorflow Model through a Website/188 Saving Tensorflow Models.en_US.srt 20.5 KB
11 Use Tensorflow to Classify Handwritten Digits/181 Understanding the Tensorflow Graph_ Nodes and Edges.en_US.srt 20.5 KB
12 Serving a Tensorflow Model through a Website/190 Converting a Model to Tensorflow.js.en_US.srt 20.3 KB
05 Predict House Prices with Multivariable Linear Regression/074 Improving the Model by Transforming the Data.en_US.srt 20.0 KB
11 Use Tensorflow to Classify Handwritten Digits/179 TensorFlow Sessions and Batching Data.en_US.srt 19.7 KB
05 Predict House Prices with Multivariable Linear Regression/084 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).en_US.srt 19.7 KB
03 Python Programming for Data Science and Machine Learning/023 [Python] - Functions - Part 2_ Arguments & Parameters.en_US.srt 19.3 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/162 Pre-processing_ Scaling Inputs and Creating a Validation Dataset.en_US.srt 19.2 KB
05 Predict House Prices with Multivariable Linear Regression/061 Working with Index Data, Pandas Series, and Dummy Variables.en_US.srt 19.1 KB
05 Predict House Prices with Multivariable Linear Regression/083 Build a Valuation Tool (Part 1)_ Working with Pandas Series & Numpy ndarrays.en_US.srt 19.1 KB
05 Predict House Prices with Multivariable Linear Regression/066 Techniques to Style Scatter Plots.en_US.srt 19.1 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/041 Understanding Partial Derivatives and How to use SymPy.en_US.srt 18.7 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/151 Costs and Disadvantages of Neural Networks.en_US.srt 18.5 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/093 Joint & Conditional Probability.en_US.srt 18.3 KB
11 Use Tensorflow to Classify Handwritten Digits/184 Prediction and Model Evaluation.en_US.srt 18.2 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/154 Making Predictions using InceptionResNet.en_US.srt 18.2 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/163 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.en_US.srt 17.9 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/130 Count the Tokens to Train the Naive Bayes Model.en_US.srt 17.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/106 Tokenizing, Removing Stop Words and the Python Set Data Structure.en_US.srt 17.6 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/161 Exploring the CIFAR Data.en_US.srt 17.5 KB
05 Predict House Prices with Multivariable Linear Regression/058 Clean and Explore the Data (Part 2)_ Find Missing Values.en_US.srt 17.2 KB
05 Predict House Prices with Multivariable Linear Regression/079 Residual Analysis (Part 1)_ Predicted vs Actual Values.en_US.srt 16.8 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/043 [Python] - Loops and Performance Considerations.en_US.srt 16.7 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/035 Understanding the Power Rule & Creating Charts with Subplots.en_US.srt 16.6 KB
12 Serving a Tensorflow Model through a Website/191 Introducing the Website Project and Tooling.en_US.srt 16.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/100 Cleaning Data (Part 1)_ Check for Empty Emails & Null Entries.en_US.srt 16.5 KB
05 Predict House Prices with Multivariable Linear Regression/064 Calculating Correlations and the Problem posed by Multicollinearity.en_US.srt 16.5 KB
12 Serving a Tensorflow Model through a Website/201 Making a Prediction from a Digit drawn on the HTML Canvas.en_US.srt 16.4 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/118 Create the Vocabulary for the Spam Classifier.en_US.srt 16.4 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/050 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).en_US.srt 16.0 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/034 LaTeX Markdown and Generating Data with Numpy.en_US.srt 15.8 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/152 Preprocessing Image Data and How RGB Works.en_US.srt 15.5 KB
03 Python Programming for Data Science and Machine Learning/028 [Python] - Tips, Code Style and Naming Conventions.en_US.srt 15.5 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [exercise_info] Python Loops Coding Exercise.html 15.5 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/115 Styling the Word Cloud with a Mask.en_US.srt 15.4 KB
03 Python Programming for Data Science and Machine Learning/018 [Python] - Variables and Types.en_US.srt 15.4 KB
03 Python Programming for Data Science and Machine Learning/024 [Python] - Functions - Part 3_ Results & Return Values.en_US.srt 15.3 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/103 Data Visualisation (Part 1)_ Pie Charts.en_US.srt 14.9 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/112 [Python] - Logical Operators to Create Subsets and Indices.en_US.srt 14.9 KB
05 Predict House Prices with Multivariable Linear Regression/057 Clean and Explore the Data (Part 1)_ Understand the Nature of the Dataset.en_US.srt 14.5 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/121 Sparse Matrix (Part 1)_ Split the Training and Testing Data.en_US.srt 14.0 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/094 Bayes Theorem.en_US.srt 14.0 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/117 Styling Word Clouds with Custom Fonts.en_US.srt 13.7 KB
05 Predict House Prices with Multivariable Linear Regression/082 Making Predictions (Part 2)_ Standard Deviation, RMSE, and Prediction Intervals.en_US.srt 13.7 KB
05 Predict House Prices with Multivariable Linear Regression/078 How to Analyse and Plot Regression Residuals.en_US.srt 13.7 KB
11 Use Tensorflow to Classify Handwritten Digits/178 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.en_US.srt 13.6 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/165 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.en_US.srt 13.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/096 Reading Files (Part 2)_ Stream Objects and Email Structure.en_US.srt 13.5 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/147 08-Naive-Bayes-with-scikit-learn.ipynb.zip 13.3 KB
05 Predict House Prices with Multivariable Linear Regression/059 Visualising Data (Part 1)_ Historams, Distributions & Outliers.en_US.srt 13.2 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/089 Gathering Email Data and Working with Archives & Text Editors.en_US.srt 13.1 KB
02 Predict Movie Box Office Revenue with Linear Regression/007 Gather & Clean the Data.en_US.srt 12.9 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/049 Understanding Nested Loops and Plotting the MSE Function (Part 1).en_US.srt 12.9 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/114 Creating your First Word Cloud.en_US.srt 12.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/125 Checkpoint_ Understanding the Data.en_US.srt 12.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/111 Advanced Subsetting on DataFrames_ the apply() Function.en_US.srt 12.5 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/048 Implementing a MSE Cost Function.en_US.srt 12.5 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/155 Coding Challenge Solution_ Using other Keras Models.en_US.srt 12.5 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/047 Transposing and Reshaping Arrays.en_US.srt 12.5 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/142 False Positive vs False Negatives.en_US.srt 12.3 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/137 Joint Conditional Probability (Part 1)_ Dot Product.en_US.srt 12.2 KB
11 Use Tensorflow to Classify Handwritten Digits/175 Data Preprocessing_ One-Hot Encoding and Creating the Validation Dataset.en_US.srt 12.2 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/042 Implementing Batch Gradient Descent with SymPy.en_US.srt 12.0 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/046 Introduction to the Mean Squared Error (MSE).en_US.srt 11.7 KB
12 Serving a Tensorflow Model through a Website/197 Data Pre-Processing for Tensorflow.js.en_US.srt 11.5 KB
05 Predict House Prices with Multivariable Linear Regression/062 Understanding Descriptive Statistics_ the Mean vs the Median.en_US.srt 11.3 KB
03 Python Programming for Data Science and Machine Learning/019 [Python] - Lists and Arrays.en_US.srt 11.2 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/123 Sparse Matrix (Part 3)_ Using groupby() and Saving .txt Files.en_US.srt 11.2 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/113 Word Clouds & How to install Additional Python Packages.en_US.srt 11.1 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/153 Importing Keras Models and the Tensorflow Graph.en_US.srt 11.0 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/095 Reading Files (Part 1)_ Absolute Paths and Relative Paths.en_US.srt 10.9 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/128 Setting up the Notebook and Understanding Delimiters in a Dataset.en_US.srt 10.7 KB
05 Predict House Prices with Multivariable Linear Regression/070 How to Shuffle and Split Training & Testing Data.en_US.srt 10.7 KB
09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 The Human Brain and the Inspiration for Artificial Neural Networks.en_US.srt 10.5 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/168 Model Evaluation and the Confusion Matrix.en_US.srt 10.4 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/108 Removing HTML tags with BeautifulSoup.en_US.srt 10.3 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/138 Joint Conditional Probablity (Part 2)_ Priors.en_US.srt 10.2 KB
02 Predict Movie Box Office Revenue with Linear Regression/009 The Intuition behind the Linear Regression Model.en_US.srt 10.0 KB
05 Predict House Prices with Multivariable Linear Regression/075 How to Interpret Coefficients using p-Values and Statistical Significance.en_US.srt 10.0 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/052 Visualising the Optimisation on a 3D Surface.en_US.srt 9.9 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/107 Word Stemming & Removing Punctuation.en_US.srt 9.9 KB
03 Python Programming for Data Science and Machine Learning/022 [Python] - Functions - Part 1_ Defining and Calling Functions.en_US.srt 9.7 KB
12 Serving a Tensorflow Model through a Website/187 What you'll make.en_US.srt 9.4 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/139 Making Predictions_ Comparing Joint Probabilities.en_US.srt 9.3 KB
12 Serving a Tensorflow Model through a Website/203 Publish and Share your Website!.en_US.srt 9.1 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/144 The Precision Metric.en_US.srt 9.1 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/132 Calculate the Token Probabilities and Save the Trained Model.en_US.srt 9.1 KB
05 Predict House Prices with Multivariable Linear Regression/071 Running a Multivariable Regression.en_US.srt 9.1 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/088 How to Translate a Business Problem into a Machine Learning Problem.en_US.srt 9.0 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/104 Data Visualisation (Part 2)_ Donut Charts.en_US.srt 8.8 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/033 Introduction to Cost Functions.en_US.srt 8.7 KB
11 Use Tensorflow to Classify Handwritten Digits/173 Getting the Data and Loading it into Numpy Arrays.en_US.srt 8.7 KB
11 Use Tensorflow to Classify Handwritten Digits/176 What is a Tensor_.en_US.srt 8.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/101 Cleaning Data (Part 2)_ Working with a DataFrame Index.en_US.srt 8.5 KB
05 Predict House Prices with Multivariable Linear Regression/060 Visualising Data (Part 2)_ Seaborn and Probability Density Functions.en_US.srt 8.3 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/045 Concatenating Numpy Arrays.en_US.srt 8.3 KB
03 Python Programming for Data Science and Machine Learning/014 Windows Users - Install Anaconda.en_US.srt 8.2 KB
02 Predict Movie Box Office Revenue with Linear Regression/006 Introduction to Linear Regression & Specifying the Problem.en_US.srt 8.1 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/109 Creating a Function for Text Processing.en_US.srt 8.0 KB
05 Predict House Prices with Multivariable Linear Regression/056 Gathering the Boston House Price Data.en_US.srt 8.0 KB
05 Predict House Prices with Multivariable Linear Regression/063 Introduction to Correlation_ Understanding Strength & Direction.en_US.srt 7.8 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/105 Introduction to Natural Language Processing (NLP).en_US.srt 7.6 KB
03 Python Programming for Data Science and Machine Learning/015 Mac Users - Install Anaconda.en_US.srt 7.5 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/131 Sum the Tokens across the Spam and Ham Subsets.en_US.srt 7.5 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/140 The Accuracy Metric.en_US.srt 7.4 KB
12 Serving a Tensorflow Model through a Website/194 Adding a Favicon.en_US.srt 7.1 KB
05 Predict House Prices with Multivariable Linear Regression/069 Understanding Multivariable Regression.en_US.srt 7.0 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/120 Coding Challenge_ Find the Longest Email.en_US.srt 7.0 KB
03 Python Programming for Data Science and Machine Learning/016 Does LSD Make You Better at Maths_.en_US.srt 6.8 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/032 How a Machine Learns.en_US.srt 6.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/099 Create a Pandas DataFrame of Email Bodies.en_US.srt 6.7 KB
11 Use Tensorflow to Classify Handwritten Digits/185 11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/102 Saving a JSON File with Pandas.en_US.srt 6.4 KB
01 Introduction to the Course/001 What is Machine Learning_.en_US.srt 6.4 KB
12 Serving a Tensorflow Model through a Website/188 11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.4 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/143 The Recall Metric.en_US.srt 6.3 KB
11 Use Tensorflow to Classify Handwritten Digits/174 Data Exploration and Understanding the Structure of the Input Data.en_US.srt 6.3 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/159 Installing Tensorflow and Keras for Jupyter.en_US.srt 6.2 KB
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05 Predict House Prices with Multivariable Linear Regression/055 Defining the Problem.en_US.srt 6.0 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/160 Gathering the CIFAR 10 Dataset.en_US.srt 5.9 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/134 07-Bayes-Classifier-Training.ipynb.zip 5.8 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/091 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.en_US.srt 5.7 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/119 Coding Challenge_ Check for Membership in a Collection.en_US.srt 5.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/116 Solving the Hamlet Challenge.en_US.srt 5.5 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/097 Extracting the Text in the Email Body.en_US.srt 5.5 KB
01 Introduction to the Course/002 What is Data Science_.en_US.srt 5.3 KB
07 Train a Naive Bayes Classifier to Create a Spam Filter_ Part 2/133 Coding Challenge_ Prepare the Test Data.en_US.srt 4.9 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/092 Basic Probability.en_US.srt 4.9 KB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/158 Solving a Business Problem with Image Classification.en_US.srt 4.8 KB
12 Serving a Tensorflow Model through a Website/193 x-test0-ylabel7.txt 4.6 KB
12 Serving a Tensorflow Model through a Website/193 x-test1-ylabel2.txt 4.6 KB
12 Serving a Tensorflow Model through a Website/193 x-test2-ylabel1.txt 4.6 KB
13 Next Steps/205 Where next_.html 4.6 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/090 How to Add the Lesson Resources to the Project.en_US.srt 4.5 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/145 The F-score or F1 Metric.en_US.srt 4.3 KB
06 Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails_ Part 1/124 Coding Challenge Solution_ Preparing the Test Data.en_US.srt 4.2 KB
05 Predict House Prices with Multivariable Linear Regression/072 How to Calculate the Model Fit with R-Squared.en_US.srt 4.1 KB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/136 Set up the Testing Notebook.en_US.srt 3.7 KB
04 Introduction to Optimisation and the Gradient Descent Algorithm/031 What's Coming Up_.en_US.srt 3.6 KB
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01 Introduction to the Course/004 Top Tips for Succeeding on this Course.html 2.7 KB
05 Predict House Prices with Multivariable Linear Regression/085 [exercise_info] Python Conditional Statement Coding Exercise.html 2.5 KB
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09 Introduction to Neural Networks and How to Use Pre-Trained Models/149 Course-Resources.txt 62 bytes
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/158 Course-Resources.txt 62 bytes
11 Use Tensorflow to Classify Handwritten Digits/172 Course-Resources.txt 62 bytes
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02 Predict Movie Box Office Revenue with Linear Regression/008 Try-Jupyter-in-your-Browser.txt 25 bytes

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