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

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

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种子哈希：efb18a1509c7236abbca990bc7b38e5c3269f8d0
文件大小： 19.23G
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收录时间：2021-03-18
最近下载：2025-05-04

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文件列表

  • 5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4 238.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4 199.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4 184.7 MB
  • 16. Career Advice + Extra Bits/9. CWD Git + Github.mp4 184.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters.mp4 184.1 MB
  • 14. Neural Networks Deep Learning/32. Training Your Deep Neural Network.mp4 174.7 MB
  • 16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4 168.8 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4 166.9 MB
  • 9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4 166.0 MB
  • 14. Neural Networks Deep Learning/34. Make And Transform Predictions.mp4 162.5 MB
  • 14. Neural Networks Deep Learning/21. Turning Data Into Batches 2.mp4 156.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4 153.3 MB
  • 5. Data Science Environment Setup/5. Mac Environment Setup.mp4 151.4 MB
  • 14. Neural Networks Deep Learning/37. Visualizing And Evaluate Model Predictions 2.mp4 150.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data.mp4 150.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4 149.2 MB
  • 14. Neural Networks Deep Learning/41. Making Predictions On Test Images.mp4 147.7 MB
  • 14. Neural Networks Deep Learning/40. Training Model On Full Dataset.mp4 146.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 146.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4 144.6 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4 144.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/14. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 143.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4 141.6 MB
  • 14. Neural Networks Deep Learning/15. Preparing The Images.mp4 140.4 MB
  • 16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 136.6 MB
  • 14. Neural Networks Deep Learning/35. Transform Predictions To Text.mp4 136.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4 133.7 MB
  • 14. Neural Networks Deep Learning/39. Saving And Loading A Trained Model.mp4 133.2 MB
  • 5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 131.6 MB
  • 8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 129.6 MB
  • 14. Neural Networks Deep Learning/22. Visualizing Our Data.mp4 127.9 MB
  • 14. Neural Networks Deep Learning/25. Building A Deep Learning Model.mp4 127.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.mp4 127.7 MB
  • 14. Neural Networks Deep Learning/42. Submitting Model to Kaggle.mp4 127.2 MB
  • 8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 125.6 MB
  • 14. Neural Networks Deep Learning/36. Visualizing Model Predictions.mp4 125.1 MB
  • 14. Neural Networks Deep Learning/43. Making Predictions On Our Images.mp4 125.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/19. Choosing The Right Model For Your Data 3 (Classification).mp4 124.6 MB
  • 16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 124.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/46. Putting It All Together 2.mp4 122.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 2.mp4 122.4 MB
  • 14. Neural Networks Deep Learning/9. Importing TensorFlow 2.mp4 122.4 MB
  • 14. Neural Networks Deep Learning/14. Loading Our Data Labels.mp4 120.4 MB
  • 14. Neural Networks Deep Learning/38. Visualizing And Evaluate Model Predictions 3.mp4 118.7 MB
  • 16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 118.5 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.mp4 113.2 MB
  • 14. Neural Networks Deep Learning/16. Turning Data Labels Into Numbers.mp4 112.7 MB
  • 6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4 111.7 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 111.5 MB
  • 14. Neural Networks Deep Learning/27. Building A Deep Learning Model 3.mp4 111.1 MB
  • 14. Neural Networks Deep Learning/26. Building A Deep Learning Model 2.mp4 111.0 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4 110.6 MB
  • 14. Neural Networks Deep Learning/19. Preprocess Images 2.mp4 110.2 MB
  • 6. Pandas Data Analysis/9. Manipulating Data.mp4 110.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 109.9 MB
  • 17. Learn Python/1. What Is A Programming Language.mp4 109.9 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.mp4 109.2 MB
  • 5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4 108.9 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4 108.4 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4 107.8 MB
  • 14. Neural Networks Deep Learning/2. Deep Learning and Unstructured Data.mp4 107.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 106.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4 105.7 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.mp4 104.8 MB
  • 8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 103.6 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.mp4 101.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 100.6 MB
  • 6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp4 100.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/37. Evaluating A Model With Scikit-learn Functions.mp4 99.4 MB
  • 17. Learn Python/16. Variables.mp4 98.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 98.0 MB
  • 17. Learn Python/2. Python Interpreter.mp4 98.0 MB
  • 8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp4 96.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 95.9 MB
  • 7. NumPy/13. Exercise Nut Butter Store Sales.mp4 95.8 MB
  • 6. Pandas Data Analysis/11. Manipulating Data 3.mp4 95.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/38. Improving A Machine Learning Model.mp4 95.4 MB
  • 14. Neural Networks Deep Learning/18. Preprocess Images.mp4 94.5 MB
  • 14. Neural Networks Deep Learning/13. Optional Reloading Colab Notebook.mp4 93.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 92.6 MB
  • 14. Neural Networks Deep Learning/20. Turning Data Into Batches.mp4 92.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).mp4 91.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).mp4 91.4 MB
  • 9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data 2 (Regression).mp4 91.1 MB
  • 6. Pandas Data Analysis/10. Manipulating Data 2.mp4 90.7 MB
  • 8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 90.6 MB
  • 14. Neural Networks Deep Learning/28. Building A Deep Learning Model 4.mp4 90.5 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.mp4 90.3 MB
  • 7. NumPy/16. Turn Images Into NumPy Arrays.mp4 90.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp4 90.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp4 89.8 MB
  • 7. NumPy/12. Dot Product vs Element Wise.mp4 88.0 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp4 86.7 MB
  • 18. Learn Python Part 2/45. Modules in Python.mp4 86.2 MB
  • 8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 86.1 MB
  • 17. Learn Python/5. Python 2 vs Python 3.mp4 86.1 MB
  • 8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 86.0 MB
  • 7. NumPy/8. Manipulating Arrays.mp4 84.6 MB
  • 14. Neural Networks Deep Learning/11. Using A GPU.mp4 84.5 MB
  • 13. Data Engineering/9. Optional OLTP Databases.mp4 83.6 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.mp4 83.2 MB
  • 14. Neural Networks Deep Learning/30. Evaluating Our Model.mp4 83.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp4 83.1 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp4 83.1 MB
  • 7. NumPy/4. NumPy DataTypes and Attributes.mp4 82.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 4 (Confusion Matrix).mp4 81.5 MB
  • 1. Introduction/1. Course Outline.mp4 81.0 MB
  • 6. Pandas Data Analysis/6. Describing Data with Pandas.mp4 79.2 MB
  • 9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 78.8 MB
  • 8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 78.3 MB
  • 18. Learn Python Part 2/2. Conditional Logic.mp4 78.2 MB
  • 14. Neural Networks Deep Learning/4. Setting Up Google Colab.mp4 77.8 MB
  • 14. Neural Networks Deep Learning/33. Evaluating Performance With TensorBoard.mp4 77.8 MB
  • 17. Learn Python/10. Numbers.mp4 76.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.mp4 76.1 MB
  • 18. Learn Python Part 2/48. Packages in Python.mp4 75.9 MB
  • 6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp4 75.9 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.mp4 75.1 MB
  • 5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp4 74.9 MB
  • 7. NumPy/7. Viewing Arrays and Matrices.mp4 74.1 MB
  • 9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 1 (R2 Score).mp4 73.8 MB
  • 8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp4 73.1 MB
  • 17. Learn Python/26. Built-In Functions + Methods.mp4 72.8 MB
  • 7. NumPy/9. Manipulating Arrays 2.mp4 71.2 MB
  • 18. Learn Python Part 2/36. Pure Functions.mp4 70.6 MB
  • 5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp4 70.6 MB
  • 8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp4 70.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp4 70.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.mp4 70.1 MB
  • 6. Pandas Data Analysis/13. How To Download The Course Assignments.mp4 70.0 MB
  • 7. NumPy/5. Creating NumPy Arrays.mp4 70.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/21. Making Predictions With Our Model.mp4 69.7 MB
  • 14. Neural Networks Deep Learning/17. Creating Our Own Validation Set.mp4 69.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).mp4 69.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp4 68.0 MB
  • 17. Learn Python/48. Sets 2.mp4 67.4 MB
  • 17. Learn Python/3. How To Run Python Code.mp4 67.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp4 66.8 MB
  • 9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 5 (Confusion Matrix).mp4 66.7 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp4 66.4 MB
  • 18. Learn Python Part 2/24. return.mp4 66.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp4 66.1 MB
  • 17. Learn Python/34. List Methods.mp4 64.8 MB
  • 3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp4 63.4 MB
  • 8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 63.3 MB
  • 17. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 62.6 MB
  • 8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 59.7 MB
  • 9. Scikit-learn Creating Machine Learning Models/44. Saving And Loading A Model 2.mp4 59.5 MB
  • 9. Scikit-learn Creating Machine Learning Models/20. Fitting A Model To The Data.mp4 59.3 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp4 58.2 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.mp4 58.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).mp4 57.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/22. predict() vs predict_proba().mp4 57.0 MB
  • 7. NumPy/11. Reshape and Transpose.mp4 56.1 MB
  • 18. Learn Python Part 2/41. List Comprehensions.mp4 55.9 MB
  • 18. Learn Python Part 2/47. Optional PyCharm.mp4 55.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model.mp4 55.2 MB
  • 18. Learn Python Part 2/40. reduce().mp4 54.8 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4 54.6 MB
  • 14. Neural Networks Deep Learning/6. Uploading Project Data.mp4 54.5 MB
  • 7. NumPy/6. NumPy Random Seed.mp4 54.4 MB
  • 7. NumPy/10. Standard Deviation and Variance.mp4 53.6 MB
  • 17. Learn Python/30. Exercise Password Checker.mp4 53.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).mp4 53.1 MB
  • 17. Learn Python/28. Exercise Type Conversion.mp4 52.8 MB
  • 18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp4 52.7 MB
  • 14. Neural Networks Deep Learning/23. Preparing Our Inputs and Outputs.mp4 52.5 MB
  • 17. Learn Python/32. List Slicing.mp4 52.3 MB
  • 18. Learn Python Part 2/18. Our First GUI.mp4 52.0 MB
  • 8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 51.9 MB
  • 17. Learn Python/23. Formatted Strings.mp4 51.6 MB
  • 17. Learn Python/24. String Indexes.mp4 51.5 MB
  • 8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 51.4 MB
  • 18. Learn Python Part 2/21. Functions.mp4 51.0 MB
  • 18. Learn Python Part 2/49. Different Ways To Import.mp4 50.3 MB
  • 5. Data Science Environment Setup/7. Windows Environment Setup.mp4 50.2 MB
  • 17. Learn Python/4. Our First Python Program.mp4 49.5 MB
  • 18. Learn Python Part 2/8. Exercise Logical Operators.mp4 48.9 MB
  • 14. Neural Networks Deep Learning/12. Optional GPU and Google Colab.mp4 48.1 MB
  • 14. Neural Networks Deep Learning/29. Summarizing Our Model.mp4 47.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model (Regression).mp4 47.1 MB
  • 3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 47.1 MB
  • 18. Learn Python Part 2/11. Iterables.mp4 45.3 MB
  • 18. Learn Python Part 2/29. args and kwargs.mp4 45.1 MB
  • 18. Learn Python Part 2/4. Truthy vs Falsey.mp4 44.9 MB
  • 2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 44.7 MB
  • 17. Learn Python/44. Dictionary Methods 2.mp4 44.4 MB
  • 14. Neural Networks Deep Learning/7. Setting Up Our Data.mp4 44.3 MB
  • 13. Data Engineering/2. What Is Data.mp4 44.3 MB
  • 17. Learn Python/11. Math Functions.mp4 43.8 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.mp4 43.6 MB
  • 9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 42.6 MB
  • 17. Learn Python/37. Common List Patterns.mp4 42.4 MB
  • 14. Neural Networks Deep Learning/5. Google Colab Workspace.mp4 41.6 MB
  • 17. Learn Python/7. Learning Python.mp4 40.4 MB
  • 18. Learn Python Part 2/37. map().mp4 40.2 MB
  • 18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp4 40.0 MB
  • 8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp4 39.9 MB
  • 18. Learn Python Part 2/32. Scope Rules.mp4 39.5 MB
  • 17. Learn Python/47. Sets.mp4 38.8 MB
  • 3. Machine Learning and Data Science Framework/7. Features In Data.mp4 38.6 MB
  • 14. Neural Networks Deep Learning/31. Preventing Overfitting.mp4 38.3 MB
  • 18. Learn Python Part 2/33. global Keyword.mp4 38.3 MB
  • 18. Learn Python Part 2/42. Set Comprehensions.mp4 37.1 MB
  • 11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp4 36.1 MB
  • 18. Learn Python Part 2/10. For Loops.mp4 36.0 MB
  • 18. Learn Python Part 2/9. is vs ==.mp4 35.2 MB
  • 12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp4 34.5 MB
  • 7. NumPy/15. Sorting Arrays.mp4 34.4 MB
  • 17. Learn Python/40. Dictionaries.mp4 34.3 MB
  • 13. Data Engineering/7. Types Of Databases.mp4 34.1 MB
  • 8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp4 33.0 MB
  • 9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).mp4 32.9 MB
  • 17. Learn Python/19. Strings.mp4 32.5 MB
  • 18. Learn Python Part 2/26. Methods vs Functions.mp4 32.2 MB
  • 5. Data Science Environment Setup/4. Conda Environments.mp4 32.0 MB
  • 2. Machine Learning 101/4. How Did We Get Here.mp4 32.0 MB
  • 3. Machine Learning and Data Science Framework/5. Types of Data.mp4 30.7 MB
  • 17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 30.7 MB
  • 17. Learn Python/8. Python Data Types.mp4 30.3 MB
  • 9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).mp4 29.9 MB
  • 18. Learn Python Part 2/13. range().mp4 29.7 MB
  • 18. Learn Python Part 2/7. Logical Operators.mp4 29.7 MB
  • 2. Machine Learning 101/1. What Is Machine Learning.mp4 29.7 MB
  • 18. Learn Python Part 2/15. While Loops.mp4 29.7 MB
  • 14. Neural Networks Deep Learning/10. Optional TensorFlow 2.0 Default Issue.mp4 29.5 MB
  • 18. Learn Python Part 2/3. Indentation In Python.mp4 29.4 MB
  • 1. Introduction/4. Your First Day.mp4 29.3 MB
  • 17. Learn Python/36. List Methods 3.mp4 29.0 MB
  • 3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4 28.9 MB
  • 6. Pandas Data Analysis/3. Pandas Introduction.mp4 28.8 MB
  • 17. Learn Python/35. List Methods 2.mp4 28.7 MB
  • 3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp4 28.7 MB
  • 17. Learn Python/43. Dictionary Methods.mp4 28.5 MB
  • 7. NumPy/2. NumPy Introduction.mp4 28.1 MB
  • 17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 27.9 MB
  • 7. NumPy/14. Comparison Operators.mp4 27.6 MB
  • 17. Learn Python/6. Exercise How Does Python Work.mp4 27.2 MB
  • 18. Learn Python Part 2/16. While Loops 2.mp4 27.2 MB
  • 17. Learn Python/45. Tuples.mp4 26.9 MB
  • 2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 26.7 MB
  • 18. Learn Python Part 2/14. enumerate().mp4 26.0 MB
  • 13. Data Engineering/5. What Is A Data Engineer 3.mp4 25.5 MB
  • 13. Data Engineering/4. What Is A Data Engineer 2.mp4 25.4 MB
  • 15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.mp4 24.7 MB
  • 18. Learn Python Part 2/38. filter().mp4 24.7 MB
  • 3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp4 24.6 MB
  • 3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp4 24.4 MB
  • 17. Learn Python/22. Escape Sequences.mp4 24.3 MB
  • 18. Learn Python Part 2/22. Parameters and Arguments.mp4 24.3 MB
  • 2. Machine Learning 101/6. Types of Machine Learning.mp4 23.9 MB
  • 18. Learn Python Part 2/17. break, continue, pass.mp4 23.3 MB
  • 18. Learn Python Part 2/43. Exercise Comprehensions.mp4 23.0 MB
  • 17. Learn Python/31. Lists.mp4 23.0 MB
  • 17. Learn Python/15. Optional bin() and complex.mp4 23.0 MB
  • 18. Learn Python Part 2/30. Exercise Functions.mp4 22.9 MB
  • 3. Machine Learning and Data Science Framework/12. Experimentation.mp4 22.4 MB
  • 18. Learn Python Part 2/39. zip().mp4 22.3 MB
  • 14. Neural Networks Deep Learning/8. Setting Up Our Data 2.mp4 21.9 MB
  • 17. Learn Python/25. Immutability.mp4 21.8 MB
  • 17. Learn Python/42. Dictionary Keys.mp4 21.4 MB
  • 18. Learn Python Part 2/1. Breaking The Flow.mp4 21.3 MB
  • 18. Learn Python Part 2/20. Exercise Find Duplicates.mp4 21.2 MB
  • 15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.mp4 21.2 MB
  • 18. Learn Python Part 2/31. Scope.mp4 21.1 MB
  • 18. Learn Python Part 2/5. Ternary Operator.mp4 20.7 MB
  • 2. Machine Learning 101/2. AIMachine LearningData Science.mp4 20.6 MB
  • 18. Learn Python Part 2/28. Clean Code.mp4 20.6 MB
  • 2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4 20.4 MB
  • 18. Learn Python Part 2/6. Short Circuiting.mp4 20.3 MB
  • 5. Data Science Environment Setup/2. Introducing Our Tools.mp4 20.2 MB
  • 13. Data Engineering/13. Kafka and Stream Processing.mp4 20.2 MB
  • 18. Learn Python Part 2/35. Why Do We Need Scope.mp4 20.1 MB
  • 17. Learn Python/33. Matrix.mp4 20.1 MB
  • 17. Learn Python/21. Type Conversion.mp4 19.9 MB
  • 15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.mp4 19.9 MB
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