[FreeCourseSite.com] Udemy - Complete 2022 Data Science & Machine Learning Bootcamp

Creation Time	Sept. 23, 2023, 12:26 p.m.
Last Access Time	Dec. 19, 2024, 10 a.m.
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Keywords	Complete FreeCourseSite Data - Learning Udemy Machine 2022 Science Bootcamp com
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Total Files	434
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04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 229.5 MB
12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image.mp4 210.4 MB
05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 200.9 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix.mp4 193.3 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate.mp4 190.1 MB
03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports.mp4 186.9 MB
12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server.mp4 175.4 MB
05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 175.2 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions.mp4 173.9 MB
11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout.mp4 173.8 MB
12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas.mp4 172.7 MB
12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas.mp4 159.3 MB
12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic.mp4 158.2 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 152.5 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts.mp4 152.0 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary.mp4 149.5 MB
12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images.mp4 147.8 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn.mp4 145.7 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 145.2 MB
03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation.mp4 138.1 MB
12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling.mp4 136.8 MB
03 - Python Programming for Data Science and Machine Learning/014 Working with Python Objects to Analyse Data.mp4 135.5 MB
12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV.mp4 133.2 MB
05 - Predict House Prices with Multivariable Linear Regression/027 Making Predictions (Part 1) MSE & R-Squared.mp4 126.6 MB
03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods.mp4 125.4 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning.mp4 124.3 MB
05 - Predict House Prices with Multivariable Linear Regression/023 Model Simplification & Baysian Information Criterion.mp4 119.7 MB
11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture.mp4 110.6 MB
05 - Predict House Prices with Multivariable Linear Regression/011 Visualising Correlations with a Heatmap.mp4 108.4 MB
05 - Predict House Prices with Multivariable Linear Regression/004 Clean and Explore the Data (Part 2) Find Missing Values.mp4 107.5 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/013 [Python] - Loops and Performance Considerations.mp4 106.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/028 Styling the Word Cloud with a Mask.mp4 105.9 MB
05 - Predict House Prices with Multivariable Linear Regression/022 Understanding VIF & Testing for Multicollinearity.mp4 105.4 MB
02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python.mp4 105.1 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/002 Create a Full Matrix.mp4 104.8 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/011 [Python] - Generator Functions & the yield Keyword.mp4 104.2 MB
05 - Predict House Prices with Multivariable Linear Regression/007 Working with Index Data, Pandas Series, and Dummy Variables.mp4 103.8 MB
12 - Serving a Tensorflow Model through a Website/002 Saving Tensorflow Models.mp4 103.7 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/006 Making Predictions using InceptionResNet.mp4 103.2 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/011 Understanding Partial Derivatives and How to use SymPy.mp4 102.7 MB
05 - Predict House Prices with Multivariable Linear Regression/029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4 102.6 MB
03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series.mp4 101.4 MB
03 - Python Programming for Data Science and Machine Learning/010 [Python] - Functions - Part 2 Arguments & Parameters.mp4 99.4 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/030 Styling Word Clouds with Custom Fonts.mp4 99.4 MB
05 - Predict House Prices with Multivariable Linear Regression/026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4 99.2 MB
11 - Use Tensorflow to Classify Handwritten Digits/009 Tensorboard Summaries and the Filewriter.mp4 98.7 MB
12 - Serving a Tensorflow Model through a Website/015 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 98.5 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 96.9 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/002 Gathering Email Data and Working with Archives & Text Editors.mp4 96.0 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/014 Reshaping and Slicing N-Dimensional Arrays.mp4 95.1 MB
12 - Serving a Tensorflow Model through a Website/004 Converting a Model to Tensorflow.js.mp4 93.6 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm.mp4 92.9 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/019 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 92.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/035 Sparse Matrix (Part 2) Data Munging with Nested Loops.mp4 91.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries.mp4 90.3 MB
05 - Predict House Prices with Multivariable Linear Regression/030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 90.1 MB
11 - Use Tensorflow to Classify Handwritten Digits/010 Understanding the Tensorflow Graph Nodes and Edges.mp4 89.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/006 Joint & Conditional Probability.mp4 88.3 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/009 Reading Files (Part 2) Stream Objects and Email Structure.mp4 87.8 MB
11 - Use Tensorflow to Classify Handwritten Digits/013 Prediction and Model Evaluation.mp4 87.3 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/021 Removing HTML tags with BeautifulSoup.mp4 86.6 MB
12 - Serving a Tensorflow Model through a Website/003 Loading a SavedModel.mp4 85.1 MB
05 - Predict House Prices with Multivariable Linear Regression/012 Techniques to Style Scatter Plots.mp4 83.9 MB
05 - Predict House Prices with Multivariable Linear Regression/010 Calculating Correlations and the Problem posed by Multicollinearity.mp4 82.5 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/007 Coding Challenge Solution Using other Keras Models.mp4 82.0 MB
05 - Predict House Prices with Multivariable Linear Regression/025 Residual Analysis (Part 1) Predicted vs Actual Values.mp4 81.5 MB
05 - Predict House Prices with Multivariable Linear Regression/020 Improving the Model by Transforming the Data.mp4 81.4 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/004 Exploring the CIFAR Data.mp4 81.2 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/003 Costs and Disadvantages of Neural Networks.mp4 76.6 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 76.6 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 76.0 MB
02 - Predict Movie Box Office Revenue with Linear Regression/005 Analyse and Evaluate the Results.mp4 75.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/038 Checkpoint Understanding the Data.mp4 74.6 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/021 Running Gradient Descent with a MSE Cost Function.mp4 74.3 MB
11 - Use Tensorflow to Classify Handwritten Digits/008 TensorFlow Sessions and Batching Data.mp4 73.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/031 Create the Vocabulary for the Spam Classifier.mp4 70.1 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/016 Data Visualisation (Part 1) Pie Charts.mp4 70.1 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/004 Preprocessing Image Data and How RGB Works.mp4 69.2 MB
12 - Serving a Tensorflow Model through a Website/005 Introducing the Website Project and Tooling.mp4 68.8 MB
03 - Python Programming for Data Science and Machine Learning/015 [Python] - Tips, Code Style and Naming Conventions.mp4 67.2 MB
11 - Use Tensorflow to Classify Handwritten Digits/011 Name Scoping and Image Visualisation in Tensorboard.mp4 66.8 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/012 Implementing Batch Gradient Descent with SymPy.mp4 65.5 MB
05 - Predict House Prices with Multivariable Linear Regression/028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4 63.7 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/003 Count the Tokens to Train the Naive Bayes Model.mp4 63.6 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/005 Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4 61.3 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.mp4 61.3 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/005 Understanding the Power Rule & Creating Charts with Subplots.mp4 59.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/034 Sparse Matrix (Part 1) Split the Training and Testing Data.mp4 58.1 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/017 Transposing and Reshaping Arrays.mp4 58.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/025 [Python] - Logical Operators to Create Subsets and Indices.mp4 57.4 MB
05 - Predict House Prices with Multivariable Linear Regression/003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4 56.7 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/024 Advanced Subsetting on DataFrames the apply() Function.mp4 55.3 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/018 Implementing a MSE Cost Function.mp4 54.5 MB
03 - Python Programming for Data Science and Machine Learning/011 [Python] - Functions - Part 3 Results & Return Values.mp4 54.1 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/001 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 54.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/007 Bayes Theorem.mp4 51.1 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/026 Word Clouds & How to install Additional Python Packages.mp4 50.0 MB
11 - Use Tensorflow to Classify Handwritten Digits/007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 49.6 MB
11 - Use Tensorflow to Classify Handwritten Digits/004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.mp4 49.3 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/005 Importing Keras Models and the Tensorflow Graph.mp4 49.2 MB
05 - Predict House Prices with Multivariable Linear Regression/021 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 49.0 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/019 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 48.9 MB
05 - Predict House Prices with Multivariable Linear Regression/002 Gathering the Boston House Price Data.mp4 47.6 MB
03 - Python Programming for Data Science and Machine Learning/005 [Python] - Variables and Types.mp4 47.6 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/002 Joint Conditional Probability (Part 1) Dot Product.mp4 47.0 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/004 LaTeX Markdown and Generating Data with Numpy.mp4 47.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/029 Solving the Hamlet Challenge.mp4 46.8 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/020 Word Stemming & Removing Punctuation.mp4 46.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/014 Cleaning Data (Part 2) Working with a DataFrame Index.mp4 46.5 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/003 Joint Conditional Probablity (Part 2) Priors.mp4 45.8 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/007 Interacting with the Operating System and the Python Try-Catch Block.mp4 45.8 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/027 Creating your First Word Cloud.mp4 45.5 MB
05 - Predict House Prices with Multivariable Linear Regression/016 How to Shuffle and Split Training & Testing Data.mp4 45.1 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/015 Saving a JSON File with Pandas.mp4 43.4 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/016 Introduction to the Mean Squared Error (MSE).mp4 43.2 MB
05 - Predict House Prices with Multivariable Linear Regression/005 Visualising Data (Part 1) Historams, Distributions & Outliers.mp4 42.6 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/007 False Positive vs False Negatives.mp4 41.4 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/033 Coding Challenge Find the Longest Email.mp4 41.1 MB
05 - Predict House Prices with Multivariable Linear Regression/008 Understanding Descriptive Statistics the Mean vs the Median.mp4 41.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/017 Data Visualisation (Part 2) Donut Charts.mp4 41.0 MB
02 - Predict Movie Box Office Revenue with Linear Regression/002 Gather & Clean the Data.mp4 40.9 MB
01 - Introduction to the Course/001 What is Machine Learning.mp4 40.4 MB
05 - Predict House Prices with Multivariable Linear Regression/017 Running a Multivariable Regression.mp4 40.2 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/011 Model Evaluation and the Confusion Matrix.mp4 40.1 MB
01 - Introduction to the Course/002 What is Data Science.mp4 39.8 MB
11 - Use Tensorflow to Classify Handwritten Digits/002 Getting the Data and Loading it into Numpy Arrays.mp4 39.7 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/008 Reading Files (Part 1) Absolute Paths and Relative Paths.mp4 39.5 MB
03 - Python Programming for Data Science and Machine Learning/002 Mac Users - Install Anaconda.mp4 39.1 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/003 Introduction to Cost Functions.mp4 39.0 MB
11 - Use Tensorflow to Classify Handwritten Digits/005 What is a Tensor.mp4 37.9 MB
05 - Predict House Prices with Multivariable Linear Regression/006 Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4 37.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/018 Introduction to Natural Language Processing (NLP).mp4 37.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/012 Create a Pandas DataFrame of Email Bodies.mp4 37.4 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/004 Making Predictions Comparing Joint Probabilities.mp4 37.1 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/022 Visualising the Optimisation on a 3D Surface.mp4 35.6 MB
12 - Serving a Tensorflow Model through a Website/001 What you'll make.mp4 35.5 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/005 Calculate the Token Probabilities and Save the Trained Model.mp4 35.3 MB
03 - Python Programming for Data Science and Machine Learning/006 [Python] - Lists and Arrays.mp4 35.1 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/009 The Precision Metric.mp4 34.5 MB
12 - Serving a Tensorflow Model through a Website/017 Publish and Share your Website!.mp4 33.3 MB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/001 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 32.7 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/015 Concatenating Numpy Arrays.mp4 32.5 MB
03 - Python Programming for Data Science and Machine Learning/001 Windows Users - Install Anaconda.mp4 32.2 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/002 Installing Tensorflow and Keras for Jupyter.mp4 31.9 MB
05 - Predict House Prices with Multivariable Linear Regression/015 Understanding Multivariable Regression.mp4 31.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/001 How to Translate a Business Problem into a Machine Learning Problem.mp4 31.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/010 Extracting the Text in the Email Body.mp4 30.5 MB
05 - Predict House Prices with Multivariable Linear Regression/001 Defining the Problem.mp4 30.0 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 29.4 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/005 The Accuracy Metric.mp4 28.7 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/006 Coding Challenge Prepare the Test Data.mp4 28.6 MB
05 - Predict House Prices with Multivariable Linear Regression/024 How to Analyse and Plot Regression Residuals.mp4 28.1 MB
03 - Python Programming for Data Science and Machine Learning/009 [Python] - Functions - Part 1 Defining and Calling Functions.mp4 27.4 MB
02 - Predict Movie Box Office Revenue with Linear Regression/001 Introduction to Linear Regression & Specifying the Problem.mp4 26.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/022 Creating a Function for Text Processing.mp4 26.4 MB
12 - Serving a Tensorflow Model through a Website/011 Data Pre-Processing for Tensorflow.js.mp4 25.6 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/004 Sum the Tokens across the Spam and Ham Subsets.mp4 24.4 MB
12 - Serving a Tensorflow Model through a Website/008 Adding a Favicon.mp4 24.3 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/18190700-SpamData.zip 22.8 MB
07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/18190704-SpamData.zip 22.3 MB
05 - Predict House Prices with Multivariable Linear Regression/018 How to Calculate the Model Fit with R-Squared.mp4 21.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18190724-SpamData.zip 21.3 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/003 Gathering the CIFAR 10 Dataset.mp4 20.6 MB
11 - Use Tensorflow to Classify Handwritten Digits/003 Data Exploration and Understanding the Structure of the Input Data.mp4 20.6 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/001 Set up the Testing Notebook.mp4 20.0 MB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/001 Solving a Business Problem with Image Classification.mp4 19.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/003 How to Add the Lesson Resources to the Project.mp4 18.9 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/037 Coding Challenge Solution Preparing the Test Data.mp4 18.9 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/008 The Recall Metric.mp4 18.4 MB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/010 The F-score or F1 Metric.mp4 16.5 MB
03 - Python Programming for Data Science and Machine Learning/003 Does LSD Make You Better at Maths.mp4 15.6 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/032 Coding Challenge Check for Membership in a Collection.mp4 14.9 MB
11 - Use Tensorflow to Classify Handwritten Digits/18194656-MNIST.zip 14.8 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/001 What's Coming Up.mp4 12.9 MB
05 - Predict House Prices with Multivariable Linear Regression/009 Introduction to Correlation Understanding Strength & Direction.mp4 12.9 MB
02 - Predict Movie Box Office Revenue with Linear Regression/004 The Intuition behind the Linear Regression Model.mp4 12.9 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/002 How a Machine Learns.mp4 10.5 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/005 Basic Probability.mp4 9.4 MB
05 - Predict House Prices with Multivariable Linear Regression/019 Introduction to Model Evaluation.mp4 7.3 MB
11 - Use Tensorflow to Classify Handwritten Digits/001 What's coming up.mp4 5.2 MB
12 - Serving a Tensorflow Model through a Website/21028926-math-garden-stub-complete.zip 4.1 MB
12 - Serving a Tensorflow Model through a Website/21028932-math-garden-stub-12.12-checkpoint.zip 4.1 MB
05 - Predict House Prices with Multivariable Linear Regression/18179918-04-Multivariable-Regression.ipynb.zip 3.5 MB
12 - Serving a Tensorflow Model through a Website/21028876-MNIST-Model-Load-Files.zip 2.8 MB
03 - Python Programming for Data Science and Machine Learning/18204473-12-Rules-to-Learn-to-Code.pdf 2.2 MB
12 - Serving a Tensorflow Model through a Website/21028894-TFJS.zip 1.5 MB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/18179908-03-Gradient-Descent.ipynb.zip 1.1 MB
06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18179924-06-Bayes-Classifier-Pre-Processing.ipynb.zip 978.0 KB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18180490-09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 571.8 KB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18188466-TF-Keras-Classification-Images.zip 501.1 KB
02 - Predict Movie Box Office Revenue with Linear Regression/9246634-cost-revenue-dirty.csv 374.7 KB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/18180294-07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 243.1 KB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/18187728-10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 120.1 KB
01 - Introduction to the Course/18162714-ML-Data-Science-Syllabus.pdf 104.0 KB
02 - Predict Movie Box Office Revenue with Linear Regression/9249290-cost-revenue-clean.csv 90.8 KB
02 - Predict Movie Box Office Revenue with Linear Regression/18175146-01-Linear-Regression-complete.ipynb.zip 75.3 KB
12 - Serving a Tensorflow Model through a Website/21028914-math-garden-stub.zip 44.0 KB
02 - Predict Movie Box Office Revenue with Linear Regression/18175084-01-Linear-Regression-checkpoint.ipynb.zip 37.6 KB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm_en.vtt 37.6 KB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1)_en.vtt 37.2 KB
03 - Python Programming for Data Science and Machine Learning/18179882-02-Python-Intro.ipynb.zip 36.4 KB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix_en.vtt 35.5 KB
12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas_en.vtt 35.4 KB
12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV_en.vtt 34.4 KB
12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling_en.vtt 33.8 KB
12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server_en.vtt 33.7 KB
12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic_en.vtt 33.6 KB
12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas_en.vtt 33.2 KB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate_en.vtt 32.6 KB
12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image_en.vtt 32.1 KB
03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports_en.vtt 31.5 KB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary_en.vtt 30.3 KB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions_en.vtt 30.2 KB
08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn_en.vtt 29.3 KB
04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2)_en.vtt 29.0 KB
11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout_en.vtt 27.0 KB
02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python_en.vtt 27.0 KB
11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture_en.vtt 26.2 KB
03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods_en.vtt 25.9 KB
10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques_en.vtt 25.1 KB
05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques_en.vtt 25.0 KB
09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning_en.vtt 24.6 KB
05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module_en.vtt 24.5 KB
03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series_en.vtt 24.4 KB
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