[FreeAllCourse.Com] Udemy - Complete Machine Learning and Data Science Zero to Mastery

Creation Time	June 3, 2024, 1:14 a.m.
Last Access Time	July 19, 2024, 8:43 a.m.
File Size	19.2 GB
Keywords	and Complete Mastery Data - FreeAllCourse Udemy Machine to Zero Learning Science Com
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Total Files	821
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5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 227.6 MB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 190.2 MB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 176.1 MB
16. Career Advice + Extra Bits/9. CWD Git + Github.mp4 176.1 MB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters.mp4 175.6 MB
14. Neural Networks Deep Learning/32. Training Your Deep Neural Network.mp4 166.6 MB
16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4 161.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 159.1 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4 158.4 MB
14. Neural Networks Deep Learning/34. Make And Transform Predictions.mp4 155.0 MB
14. Neural Networks Deep Learning/21. Turning Data Into Batches 2.mp4 149.4 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 146.2 MB
5. Data Science Environment Setup/5. Mac Environment Setup.mp4 144.4 MB
14. Neural Networks Deep Learning/37. Visualizing And Evaluate Model Predictions 2.mp4 143.8 MB
9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data.mp4 143.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 142.3 MB
14. Neural Networks Deep Learning/41. Making Predictions On Test Images.mp4 140.8 MB
14. Neural Networks Deep Learning/40. Training Model On Full Dataset.mp4 139.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 139.3 MB
11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4 137.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 137.8 MB
9. Scikit-learn Creating Machine Learning Models/14. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 136.9 MB
9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 135.0 MB
14. Neural Networks Deep Learning/15. Preparing The Images.mp4 133.9 MB
16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 130.3 MB
14. Neural Networks Deep Learning/35. Transform Predictions To Text.mp4 129.9 MB
11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4 127.5 MB
14. Neural Networks Deep Learning/39. Saving And Loading A Trained Model.mp4 127.0 MB
5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 125.5 MB
8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 123.6 MB
14. Neural Networks Deep Learning/22. Visualizing Our Data.mp4 122.0 MB
14. Neural Networks Deep Learning/25. Building A Deep Learning Model.mp4 121.9 MB
9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.mp4 121.8 MB
14. Neural Networks Deep Learning/42. Submitting Model to Kaggle.mp4 121.3 MB
8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 119.8 MB
14. Neural Networks Deep Learning/36. Visualizing Model Predictions.mp4 119.3 MB
14. Neural Networks Deep Learning/43. Making Predictions On Our Images.mp4 119.2 MB
9. Scikit-learn Creating Machine Learning Models/19. Choosing The Right Model For Your Data 3 (Classification).mp4 118.9 MB
16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 118.4 MB
9. Scikit-learn Creating Machine Learning Models/46. Putting It All Together 2.mp4 116.9 MB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 2.mp4 116.8 MB
14. Neural Networks Deep Learning/9. Importing TensorFlow 2.mp4 116.8 MB
14. Neural Networks Deep Learning/14. Loading Our Data Labels.mp4 114.8 MB
14. Neural Networks Deep Learning/38. Visualizing And Evaluate Model Predictions 3.mp4 113.2 MB
16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 113.0 MB
11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.mp4 108.0 MB
14. Neural Networks Deep Learning/16. Turning Data Labels Into Numbers.mp4 107.5 MB
6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4 106.5 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 106.3 MB
14. Neural Networks Deep Learning/27. Building A Deep Learning Model 3.mp4 105.9 MB
14. Neural Networks Deep Learning/26. Building A Deep Learning Model 2.mp4 105.9 MB
11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4 105.5 MB
14. Neural Networks Deep Learning/19. Preprocess Images 2.mp4 105.1 MB
6. Pandas Data Analysis/9. Manipulating Data.mp4 105.0 MB
9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 104.8 MB
17. Learn Python/1. What Is A Programming Language.mp4 104.8 MB
11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.mp4 104.1 MB
5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4 103.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 103.3 MB
11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4 102.8 MB
14. Neural Networks Deep Learning/2. Deep Learning and Unstructured Data.mp4 102.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 101.3 MB
11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4 100.8 MB
11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.mp4 99.9 MB
8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 98.8 MB
11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.mp4 96.4 MB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96.0 MB
6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp4 95.4 MB
9. Scikit-learn Creating Machine Learning Models/37. Evaluating A Model With Scikit-learn Functions.mp4 94.8 MB
17. Learn Python/16. Variables.mp4 93.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 93.5 MB
17. Learn Python/2. Python Interpreter.mp4 93.5 MB
8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp4 92.2 MB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 91.5 MB
7. NumPy/13. Exercise Nut Butter Store Sales.mp4 91.3 MB
6. Pandas Data Analysis/11. Manipulating Data 3.mp4 91.0 MB
9. Scikit-learn Creating Machine Learning Models/38. Improving A Machine Learning Model.mp4 90.9 MB
14. Neural Networks Deep Learning/18. Preprocess Images.mp4 90.1 MB
14. Neural Networks Deep Learning/13. Optional Reloading Colab Notebook.mp4 88.7 MB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 88.3 MB
14. Neural Networks Deep Learning/20. Turning Data Into Batches.mp4 87.8 MB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).mp4 87.2 MB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).mp4 87.1 MB
9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data 2 (Regression).mp4 86.9 MB
6. Pandas Data Analysis/10. Manipulating Data 2.mp4 86.5 MB
8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 86.4 MB
14. Neural Networks Deep Learning/28. Building A Deep Learning Model 4.mp4 86.3 MB
11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.mp4 86.1 MB
7. NumPy/16. Turn Images Into NumPy Arrays.mp4 85.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 85.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 85.7 MB
7. NumPy/12. Dot Product vs Element Wise.mp4 83.9 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 82.7 MB
18. Learn Python Part 2/45. Modules in Python.mp4 82.2 MB
8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 82.2 MB
17. Learn Python/5. Python 2 vs Python 3.mp4 82.1 MB
8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 82.0 MB
7. NumPy/8. Manipulating Arrays.mp4 80.7 MB
14. Neural Networks Deep Learning/11. Using A GPU.mp4 80.6 MB
13. Data Engineering/9. Optional OLTP Databases.mp4 79.7 MB
11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.mp4 79.4 MB
14. Neural Networks Deep Learning/30. Evaluating Our Model.mp4 79.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 79.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 79.2 MB
7. NumPy/4. NumPy DataTypes and Attributes.mp4 79.0 MB
9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 4 (Confusion Matrix).mp4 77.7 MB
1. Introduction/1. Course Outline.mp4 77.3 MB
6. Pandas Data Analysis/6. Describing Data with Pandas.mp4 75.6 MB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 75.1 MB
8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 74.7 MB
18. Learn Python Part 2/2. Conditional Logic.mp4 74.6 MB
14. Neural Networks Deep Learning/4. Setting Up Google Colab.mp4 74.2 MB
14. Neural Networks Deep Learning/33. Evaluating Performance With TensorBoard.mp4 74.2 MB
17. Learn Python/10. Numbers.mp4 72.7 MB
11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.mp4 72.6 MB
18. Learn Python Part 2/48. Packages in Python.mp4 72.4 MB
6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp4 72.3 MB
11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.mp4 71.6 MB
5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp4 71.4 MB
7. NumPy/7. Viewing Arrays and Matrices.mp4 70.6 MB
9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 1 (R2 Score).mp4 70.4 MB
8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp4 69.7 MB
17. Learn Python/26. Built-In Functions + Methods.mp4 69.4 MB
7. NumPy/9. Manipulating Arrays 2.mp4 67.9 MB
18. Learn Python Part 2/36. Pure Functions.mp4 67.4 MB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp4 67.3 MB
8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 67.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 66.9 MB
11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.mp4 66.9 MB
6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 66.8 MB
7. NumPy/5. Creating NumPy Arrays.mp4 66.8 MB
9. Scikit-learn Creating Machine Learning Models/21. Making Predictions With Our Model.mp4 66.5 MB
14. Neural Networks Deep Learning/17. Creating Our Own Validation Set.mp4 66.4 MB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).mp4 66.0 MB
11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp4 64.8 MB
17. Learn Python/48. Sets 2.mp4 64.3 MB
17. Learn Python/3. How To Run Python Code.mp4 63.9 MB
9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 63.7 MB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 5 (Confusion Matrix).mp4 63.6 MB
11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp4 63.3 MB
18. Learn Python Part 2/24. return.mp4 63.0 MB
11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp4 63.0 MB
17. Learn Python/34. List Methods.mp4 61.8 MB
3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 60.5 MB
8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 60.3 MB
17. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 59.7 MB
8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 57.0 MB
9. Scikit-learn Creating Machine Learning Models/44. Saving And Loading A Model 2.mp4 56.8 MB
9. Scikit-learn Creating Machine Learning Models/20. Fitting A Model To The Data.mp4 56.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 55.5 MB
11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.mp4 55.3 MB
9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).mp4 54.9 MB
9. Scikit-learn Creating Machine Learning Models/22. predict() vs predict_proba().mp4 54.3 MB
7. NumPy/11. Reshape and Transpose.mp4 53.5 MB
18. Learn Python Part 2/41. List Comprehensions.mp4 53.3 MB
18. Learn Python Part 2/47. Optional PyCharm.mp4 53.1 MB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model.mp4 52.6 MB
18. Learn Python Part 2/40. reduce().mp4 52.3 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 52.0 MB
14. Neural Networks Deep Learning/6. Uploading Project Data.mp4 52.0 MB
7. NumPy/6. NumPy Random Seed.mp4 51.9 MB
7. NumPy/10. Standard Deviation and Variance.mp4 51.2 MB
17. Learn Python/30. Exercise Password Checker.mp4 51.1 MB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).mp4 50.6 MB
17. Learn Python/28. Exercise Type Conversion.mp4 50.3 MB
18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp4 50.2 MB
14. Neural Networks Deep Learning/23. Preparing Our Inputs and Outputs.mp4 50.1 MB
17. Learn Python/32. List Slicing.mp4 49.9 MB
18. Learn Python Part 2/18. Our First GUI.mp4 49.6 MB
8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 49.5 MB
17. Learn Python/23. Formatted Strings.mp4 49.3 MB
17. Learn Python/24. String Indexes.mp4 49.2 MB
8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 49.0 MB
18. Learn Python Part 2/21. Functions.mp4 48.6 MB
18. Learn Python Part 2/49. Different Ways To Import.mp4 48.0 MB
5. Data Science Environment Setup/7. Windows Environment Setup.mp4 47.9 MB
17. Learn Python/4. Our First Python Program.mp4 47.2 MB
18. Learn Python Part 2/8. Exercise Logical Operators.mp4 46.6 MB
14. Neural Networks Deep Learning/12. Optional GPU and Google Colab.mp4 45.9 MB
14. Neural Networks Deep Learning/29. Summarizing Our Model.mp4 45.4 MB
9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model (Regression).mp4 44.9 MB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 44.9 MB
18. Learn Python Part 2/11. Iterables.mp4 43.2 MB
18. Learn Python Part 2/29. args and kwargs.mp4 43.0 MB
18. Learn Python Part 2/4. Truthy vs Falsey.mp4 42.8 MB
2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 42.6 MB
17. Learn Python/44. Dictionary Methods 2.mp4 42.4 MB
14. Neural Networks Deep Learning/7. Setting Up Our Data.mp4 42.3 MB
13. Data Engineering/2. What Is Data.mp4 42.2 MB
17. Learn Python/11. Math Functions.mp4 41.8 MB
11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.mp4 41.5 MB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 40.6 MB
17. Learn Python/37. Common List Patterns.mp4 40.5 MB
14. Neural Networks Deep Learning/5. Google Colab Workspace.mp4 39.6 MB
17. Learn Python/7. Learning Python.mp4 38.5 MB
18. Learn Python Part 2/37. map().mp4 38.4 MB
18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp4 38.1 MB
8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp4 38.1 MB
18. Learn Python Part 2/32. Scope Rules.mp4 37.7 MB
17. Learn Python/47. Sets.mp4 37.0 MB
3. Machine Learning and Data Science Framework/7. Features In Data.mp4 36.8 MB
14. Neural Networks Deep Learning/31. Preventing Overfitting.mp4 36.5 MB
18. Learn Python Part 2/33. global Keyword.mp4 36.5 MB
18. Learn Python Part 2/42. Set Comprehensions.mp4 35.4 MB
11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp4 34.4 MB
18. Learn Python Part 2/10. For Loops.mp4 34.3 MB
18. Learn Python Part 2/9. is vs ==.mp4 33.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 32.9 MB
7. NumPy/15. Sorting Arrays.mp4 32.8 MB
17. Learn Python/40. Dictionaries.mp4 32.7 MB
13. Data Engineering/7. Types Of Databases.mp4 32.6 MB
8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp4 31.5 MB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).mp4 31.4 MB
17. Learn Python/19. Strings.mp4 31.0 MB
18. Learn Python Part 2/26. Methods vs Functions.mp4 30.7 MB
5. Data Science Environment Setup/4. Conda Environments.mp4 30.6 MB
2. Machine Learning 101/4. How Did We Get Here.mp4 30.5 MB
3. Machine Learning and Data Science Framework/5. Types of Data.mp4 29.3 MB
17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 29.2 MB
17. Learn Python/8. Python Data Types.mp4 28.8 MB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).mp4 28.5 MB
18. Learn Python Part 2/13. range().mp4 28.3 MB
18. Learn Python Part 2/7. Logical Operators.mp4 28.3 MB
2. Machine Learning 101/1. What Is Machine Learning.mp4 28.3 MB
18. Learn Python Part 2/15. While Loops.mp4 28.3 MB
14. Neural Networks Deep Learning/10. Optional TensorFlow 2.0 Default Issue.mp4 28.1 MB
18. Learn Python Part 2/3. Indentation In Python.mp4 28.0 MB
1. Introduction/4. Your First Day.mp4 27.9 MB
17. Learn Python/36. List Methods 3.mp4 27.7 MB
3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 27.5 MB
6. Pandas Data Analysis/3. Pandas Introduction.mp4 27.4 MB
17. Learn Python/35. List Methods 2.mp4 27.4 MB
3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 27.3 MB
17. Learn Python/43. Dictionary Methods.mp4 27.2 MB
7. NumPy/2. NumPy Introduction.mp4 26.8 MB
17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 26.6 MB
7. NumPy/14. Comparison Operators.mp4 26.4 MB
17. Learn Python/6. Exercise How Does Python Work.mp4 26.0 MB
18. Learn Python Part 2/16. While Loops 2.mp4 25.9 MB
17. Learn Python/45. Tuples.mp4 25.6 MB
2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 25.5 MB
18. Learn Python Part 2/14. enumerate().mp4 24.8 MB
13. Data Engineering/5. What Is A Data Engineer 3.mp4 24.3 MB
13. Data Engineering/4. What Is A Data Engineer 2.mp4 24.2 MB
15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.mp4 23.6 MB
18. Learn Python Part 2/38. filter().mp4 23.6 MB
3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 23.5 MB
3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 23.3 MB
17. Learn Python/22. Escape Sequences.mp4 23.2 MB
18. Learn Python Part 2/22. Parameters and Arguments.mp4 23.2 MB
2. Machine Learning 101/6. Types of Machine Learning.mp4 22.7 MB
18. Learn Python Part 2/17. break, continue, pass.mp4 22.2 MB
18. Learn Python Part 2/43. Exercise Comprehensions.mp4 22.0 MB
17. Learn Python/31. Lists.mp4 22.0 MB
17. Learn Python/15. Optional bin() and complex.mp4 21.9 MB
18. Learn Python Part 2/30. Exercise Functions.mp4 21.8 MB
3. Machine Learning and Data Science Framework/12. Experimentation.mp4 21.3 MB
18. Learn Python Part 2/39. zip().mp4 21.3 MB
14. Neural Networks Deep Learning/8. Setting Up Our Data 2.mp4 20.9 MB
17. Learn Python/25. Immutability.mp4 20.8 MB
17. Learn Python/42. Dictionary Keys.mp4 20.4 MB
18. Learn Python Part 2/1. Breaking The Flow.mp4 20.3 MB
18. Learn Python Part 2/20. Exercise Find Duplicates.mp4 20.3 MB
15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.mp4 20.2 MB
18. Learn Python Part 2/31. Scope.mp4 20.1 MB
18. Learn Python Part 2/5. Ternary Operator.mp4 19.7 MB
2. Machine Learning 101/2. AIMachine LearningData Science.mp4 19.7 MB
18. Learn Python Part 2/28. Clean Code.mp4 19.7 MB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 19.4 MB
18. Learn Python Part 2/6. Short Circuiting.mp4 19.4 MB
5. Data Science Environment Setup/2. Introducing Our Tools.mp4 19.3 MB
13. Data Engineering/13. Kafka and Stream Processing.mp4 19.2 MB
18. Learn Python Part 2/35. Why Do We Need Scope.mp4 19.2 MB
17. Learn Python/33. Matrix.mp4 19.1 MB
17. Learn Python/21. Type Conversion.mp4 19.0 MB
15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.mp4 19.0 MB
15. Storytelling + Communication How To Present Your Work/3. Communicating With Managers.mp4 18.4 MB
18. Learn Python Part 2/34. nonlocal Keyword.mp4 18.3 MB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 17.8 MB
18. Learn Python Part 2/27. Docstrings.mp4 17.3 MB
17. Learn Python/46. Tuples 2.mp4 17.0 MB
9. Scikit-learn Creating Machine Learning Models/42. Quick Tip Correlation Analysis.mp4 16.9 MB
17. Learn Python/27. Booleans.mp4 16.6 MB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 16.5 MB
18. Learn Python Part 2/12. Exercise Tricky Counter.mp4 16.4 MB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16.0 MB
16. Career Advice + Extra Bits/7. JTS Start With Why.mp4 15.4 MB
17. Learn Python/18. Augmented Assignment Operator.mp4 15.3 MB
13. Data Engineering/3. What Is A Data Engineer.mp4 15.2 MB
13. Data Engineering/6. What Is A Data Engineer 4.mp4 14.9 MB
15. Storytelling + Communication How To Present Your Work/6. Communicating With Outside World.mp4 14.5 MB
17. Learn Python/13. Operator Precedence.mp4 14.4 MB
17. Learn Python/38. List Unpacking.mp4 13.9 MB
13. Data Engineering/1. Data Engineering Introduction.mp4 13.5 MB
3. Machine Learning and Data Science Framework/1. Section Overview.mp4 13.4 MB
7. NumPy/1. Section Overview.mp4 13.3 MB
5. Data Science Environment Setup/3. What is Conda.mp4 12.5 MB
9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4 12.5 MB
8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.3 MB
14. Neural Networks Deep Learning/1. Section Overview.mp4 12.2 MB
15. Storytelling + Communication How To Present Your Work/7. Storytelling.mp4 12.0 MB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.4 MB
16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.1 MB
20. Where To Go From Here/2. Thank You.mp4 11.1 MB
9. Scikit-learn Creating Machine Learning Models/18. Quick Tip How ML Algorithms Work.mp4 11.1 MB
17. Learn Python/17. Expressions vs Statements.mp4 11.0 MB
15. Storytelling + Communication How To Present Your Work/1. Section Overview.mp4 10.9 MB
6. Pandas Data Analysis/1. Section Overview.mp4 10.9 MB
11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.mp4 10.2 MB
13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4 10.1 MB
4. The 2 Paths/1. The 2 Paths.mp4 9.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4 9.0 MB
8. Matplotlib Plotting and Data Visualization/1. Section Overview.mp4 8.6 MB
17. Learn Python/39. None.mp4 7.9 MB
17. Learn Python/20. String Concatenation.mp4 7.3 MB
7. NumPy/16.1 numpy-images.zip 7.3 MB
5. Data Science Environment Setup/1. Section Overview.mp4 6.0 MB
13. Data Engineering/12. Apache Spark and Apache Flink.mp4 5.8 MB
2. Machine Learning 101/9. Section Review.mp4 5.6 MB
8. Matplotlib Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png 654.8 KB
8. Matplotlib Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png 369.4 KB
6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png 333.2 KB
6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png 333.2 KB
5. Data Science Environment Setup/11.1 6-step-ml-framework.png 324.2 KB
5. Data Science Environment Setup/3.2 conda-cheatsheet.pdf 201.3 KB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt 31.7 KB
5. Data Science Environment Setup/8. Windows Environment Setup 2.srt 31.6 KB
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21. Extras/1. Bonus Special Thank You Gift!.html 1.6 KB
16. Career Advice + Extra Bits/14. Exercise Contribute To Open Source.html 1.4 KB
17. Learn Python/20. String Concatenation.srt 1.4 KB
7. NumPy/3. Quick Note Correction In Next Video.html 1.2 KB
18. Learn Python Part 2/44. Python Exam Testing Your Understanding.html 1.1 KB
6. Pandas Data Analysis/5. Data from URLs.html 1.1 KB
5. Data Science Environment Setup/9. Linux Environment Setup.html 1.0 KB
7. NumPy/18. Optional Extra NumPy resources.html 1.0 KB
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9. Scikit-learn Creating Machine Learning Models/5. Quick Note Upcoming Videos.html 1018 bytes
3. Machine Learning and Data Science Framework/14. Optional Elements of AI.html 975 bytes
6. Pandas Data Analysis/2. Downloading Workbooks and Assignments.html 967 bytes
18. Learn Python Part 2/50. Next Steps.html 959 bytes
16. Career Advice + Extra Bits/13. Coding Challenges.html 948 bytes
10. Supervised Learning Classification + Regression/1. Milestone Projects!.html 738 bytes
4. The 2 Paths/2. Python + Machine Learning Monthly.html 734 bytes
19. Bonus Learn Advanced Statistics and Mathematics for FREE!/1. Statistics and Mathematics.html 710 bytes
16. Career Advice + Extra Bits/1. Endorsements On LinkedIn.html 688 bytes
17. Learn Python/14. Exercise Operator Precedence.html 683 bytes
8. Matplotlib Plotting and Data Visualization/10. Quick Note Regular Expressions.html 632 bytes
16. Career Advice + Extra Bits/2. Quick Note Upcoming Video.html 587 bytes
14. Neural Networks Deep Learning/3. Setting Up With Google.html 568 bytes
16. Career Advice + Extra Bits/5. Quick Note Upcoming Videos.html 565 bytes
13. Data Engineering/8. Quick Note Upcoming Video.html 481 bytes
18. Learn Python Part 2/46. Quick Note Upcoming Videos.html 448 bytes
13. Data Engineering/10. Optional Learn SQL.html 410 bytes
18. Learn Python Part 2/25. Exercise Tesla.html 402 bytes
9. Scikit-learn Creating Machine Learning Models/3. Quick Note Upcoming Video.html 390 bytes
6. Pandas Data Analysis/7.1 car-sales.csv 369 bytes
16. Career Advice + Extra Bits/8. Quick Note Upcoming Videos.html 352 bytes
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6. Pandas Data Analysis/9.2 car-sales-missing-data.csv 287 bytes
17. Learn Python/9. How To Succeed.html 280 bytes
9. Scikit-learn Creating Machine Learning Models/17. Quick Note Decision Trees.html 221 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.1 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html 214 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/19.2 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.3 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html 208 bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.3 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
11. Milestone Project 1 Supervised Learning (Classification)/21.1 End-to-end Heart Disease Classification Notebook (same as in videos).html 207 bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.2 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
11. Milestone Project 1 Supervised Learning (Classification)/21.2 End-to-end Heart Disease Classification Notebook (with annotations).html 201 bytes
9. Scikit-learn Creating Machine Learning Models/2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html 197 bytes
9. Scikit-learn Creating Machine Learning Models/46.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html 197 bytes
8. Matplotlib Plotting and Data Visualization/19.1 Introduction to Matplotlib Notebook (from the videos).html 195 bytes
8. Matplotlib Plotting and Data Visualization/2.1 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html 195 bytes
9. Scikit-learn Creating Machine Learning Models/6.1 Scikit-Learn Reference Notebook.html 194 bytes
9. Scikit-learn Creating Machine Learning Models/7.1 Example Scikit-Learn Workflow Notebook.html 192 bytes
14. Neural Networks Deep Learning/43.1 End-to-end Dog Vision Notebook (from the videos).html 191 bytes
6. Pandas Data Analysis/11.1 Introduction to Pandas Jupyter Notebook (from the videos).html 191 bytes
6. Pandas Data Analysis/3.4 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html 191 bytes
9. Scikit-learn Creating Machine Learning Models/2.3 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
9. Scikit-learn Creating Machine Learning Models/46.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html 191 bytes
7. NumPy/16.2 Introduction to NumPy Jupyter Notebook (from the videos).html 190 bytes
7. NumPy/2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html 190 bytes
14. Neural Networks Deep Learning/43.2 End-to-end Dog Vision Notebook (with annotations).html 185 bytes
6. Pandas Data Analysis/11.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
6. Pandas Data Analysis/3.2 Introduction to Pandas Jupyter Notebook (with annotations).html 185 bytes
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7. NumPy/2.1 Introduction to NumPy Jupyter Notebook (with annotations).html 184 bytes
14. Neural Networks Deep Learning/4.3 End-to-end Dog Vision Notebook (the project we'll be working through).html 182 bytes
14. Neural Networks Deep Learning/42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html 180 bytes
14. Neural Networks Deep Learning/27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html 172 bytes
5. Data Science Environment Setup/10.1 Conda documentation on sharing an environment.html 172 bytes
14. Neural Networks Deep Learning/41.1 Dog Vision Prediction Probabilities Array.html 170 bytes
18. Learn Python Part 2/4.1 Truthy vs Falsey Stackoverflow.html 170 bytes
14. Neural Networks Deep Learning/28.1 [Article] How to choose loss & activation functions when building a deep learning model.html 169 bytes
5. Data Science Environment Setup/3.1 Getting your computer ready for machine learning How.html 167 bytes
14. Neural Networks Deep Learning/27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html 163 bytes
17. Learn Python/5.1 Python 2 vs Python 3.html 161 bytes
2. Machine Learning 101/7. Are You Getting It Yet.html 160 bytes
11. Milestone Project 1 Supervised Learning (Classification)/2.1 Structured Data Projects on GitHub.html 155 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.4 Structured Data Projects on GitHub.html 155 bytes
3. Machine Learning and Data Science Framework/3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html 147 bytes
6. Pandas Data Analysis/9.1 Jake VanderPlas's Data Manipulation with Pandas.html 146 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/9.1 Pandas Categorical Datatype Documentation.html 143 bytes
15. Storytelling + Communication How To Present Your Work/2.1 How to Think About Communicating and Sharing Your Work (blog post).html 142 bytes
5. Data Science Environment Setup/3.3 Getting started with Conda (documentation).html 139 bytes
14. Neural Networks Deep Learning/31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 136 bytes
14. Neural Networks Deep Learning/30.1 TensorBoard Callback Documentation.html 134 bytes
9. Scikit-learn Creating Machine Learning Models/15.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html 133 bytes
14. Neural Networks Deep Learning/25.2 MobileNetV2 (the model we're using) on TensorFlow Hub.html 132 bytes
6. Pandas Data Analysis/3.3 10-minutes to pandas (from the pandas documentation).html 132 bytes
14. Neural Networks Deep Learning/10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html 129 bytes
14. Neural Networks Deep Learning/14.1 Documentation on how many images Google recommends for image problems.html 129 bytes
14. Neural Networks Deep Learning/35.1 TensorFlow documentation for the unbatch() function.html 127 bytes
13. Data Engineering/7.2 OLTP vs OLAP.html 126 bytes
14. Neural Networks Deep Learning/4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html 119 bytes
17. Learn Python/43.1 Dictionary Methods.html 119 bytes
7. NumPy/12.1 Matrix Multiplication Explained.html 119 bytes
12. Milestone Project 2 Supervised Learning (Time Series Data)/2.1 Kaggle Bluebook for Bulldozers Competition.html 118 bytes
14. Neural Networks Deep Learning/21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html 118 bytes
13. Data Engineering/7.1 A Primer on ACID Transactions.html 117 bytes
17. Learn Python/16.1 Python Keywords.html 117 bytes
17. Learn Python/35.1 Python Keywords.html 117 bytes
5. Data Science Environment Setup/11.4 Dataquest Jupyter Notebook for Beginners Tutorial.html 117 bytes
14. Neural Networks Deep Learning/12.2 Introduction to Google Colab example notebook.html 116 bytes
14. Neural Networks Deep Learning/4.4 Introduction to Google Colab example notebook.html 116 bytes
17. Learn Python/18.1 Exercise Repl.html 116 bytes
7. NumPy/10.1 Standard deviation and variance explained.html 116 bytes
7. NumPy/8.1 Standard deviation and variance explained.html 116 bytes
7. NumPy/9.1 Standard deviation and variance explained.html 116 bytes
14. Neural Networks Deep Learning/6.1 Kaggle Dog Breed Identification Competition Data.html 115 bytes
17. Learn Python/26.2 String Methods.html 115 bytes
14. Neural Networks Deep Learning/11.1 Google Colab example GPU usage.html 114 bytes
14. Neural Networks Deep Learning/12.1 Google Colab Example of GPU speed up versus CPU.html 114 bytes
14. Neural Networks Deep Learning/18.2 Documentation for loading images in TensorFlow.html 114 bytes
17. Learn Python/46.1 Tuple Methods.html 114 bytes
14. Neural Networks Deep Learning/4.5 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 bytes
14. Neural Networks Deep Learning/6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html 113 bytes
17. Learn Python/34.1 List Methods.html 113 bytes
17. Learn Python/48.1 Sets Methods.html 112 bytes
17. Learn Python/15.1 Base Numbers.html 111 bytes
5. Data Science Environment Setup/11.2 Jupyter Notebook documentation.html 111 bytes
14. Neural Networks Deep Learning/5.2 Google Colab FAQ (things you should know about Google Colab).html 110 bytes
17. Learn Python/26.1 Built in Functions.html 109 bytes
14. Neural Networks Deep Learning/17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html 108 bytes
14. Neural Networks Deep Learning/26.1 Keras in TensorFlow Overview Documentation.html 108 bytes
18. Learn Python Part 2/30.1 Solution Repl.html 108 bytes
6. Pandas Data Analysis/13.1 Course notebooks - Github.html 108 bytes
9. Scikit-learn Creating Machine Learning Models/2.2 Scikit-Learn Documentation.html 108 bytes
14. Neural Networks Deep Learning/27.1 The Softmax Function (activation function we use in our model).html 107 bytes
5. Data Science Environment Setup/5.1 Miniconda download documentation.html 107 bytes
5. Data Science Environment Setup/7.1 Miniconda download documentation.html 107 bytes
15. Storytelling + Communication How To Present Your Work/6.1 fast_template by fast.ai (a template you can use for your blog on GitHub Pages).html 106 bytes
17. Learn Python/13.1 Exercise Repl.html 106 bytes
17. Learn Python/14.1 Exercise Repl.html 106 bytes
17. Learn Python/29.1 Python Comments Best Practices.html 106 bytes
6. Pandas Data Analysis/3.1 Pandas Documentation.html 106 bytes
17. Learn Python/10.1 Floating point numbers.html 104 bytes
17. Learn Python/23.1 Exercise Repl.html 104 bytes
17. Learn Python/5.2 The Story of Python.html 104 bytes
8. Matplotlib Plotting and Data Visualization/2.2 Matplotlib Documentation.html 103 bytes
18. Learn Python Part 2/20.1 Solution Repl.html 102 bytes
18. Learn Python Part 2/43.1 Solution Repl.html 102 bytes
17. Learn Python/24.1 Exercise Repl.html 101 bytes
2. Machine Learning 101/3.1 Teachable Machine.html 101 bytes
18. Learn Python Part 2/43.2 Exercise Repl.html 100 bytes
18. Learn Python Part 2/18.1 Solution Repl.html 99 bytes
18. Learn Python Part 2/18.2 Exercise Repl.html 99 bytes
14. Neural Networks Deep Learning/18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html 98 bytes
17. Learn Python/44.1 Exercise Repl.html 97 bytes
14. Neural Networks Deep Learning/25.3 Andrei Karpathy's talk on AI at Tesla.html 95 bytes
14. Neural Networks Deep Learning/4.2 Google Colab (our workspace for the upcoming project).html 95 bytes
14. Neural Networks Deep Learning/5.1 Google Colab (our workspace for the upcoming project).html 95 bytes
18. Learn Python Part 2/34.1 Solution Repl.html 95 bytes
6. Pandas Data Analysis/13.2 Google Colab.html 95 bytes
17. Learn Python/35.2 Exercise Repl.html 94 bytes
17. Learn Python/37.1 Exercise Repl.html 94 bytes
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5. Data Science Environment Setup/3.4 Conda documentation.html 93 bytes
13. Data Engineering/2.1 Kaggle.html 92 bytes
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18. Learn Python Part 2/12.1 Solution Repl.html 92 bytes
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15. Storytelling + Communication How To Present Your Work/6.2 Devblog by Hashnode (an easy and free way to create a blog you own).html 89 bytes
14. Neural Networks Deep Learning/25.4 Papers with Code (a great resource for some of the best machine learning papers with code examples).html 88 bytes
2. Machine Learning 101/5.1 Machine Learning Playground.html 88 bytes
14. Neural Networks Deep Learning/25.5 PyTorch Hub (PyTorch version of TensorFlow Hub).html 85 bytes
7. NumPy/2.3 NumPy Documentation.html 83 bytes
14. Neural Networks Deep Learning/23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 bytes
14. Neural Networks Deep Learning/25.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html 79 bytes
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