种子简介

种子名称： [FreeCourseSite.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery
文件类型： 视频
文件数目： 318个文件
文件大小： 19.22 GB
收录时间： 2020-6-6 08:14
已经下载： 3次
资源热度： 229
最近下载： 2024-12-3 16:45

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:b92656c6e2688643616f42a4e889346134681eb6&dn=[FreeCourseSite.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCourseSite.com] Udemy - Complete Machine Learning and Data Science Zero to Mastery.torrent

1. Introduction/1. Course Outline.mp477.27MB

1. Introduction/4. Your First Day.mp427.92MB

11. Milestone Project 1 Supervised Learning (Classification)/1. Section Overview.mp410.2MB

11. Milestone Project 1 Supervised Learning (Classification)/10. Preparing Our Data For Machine Learning.mp472.61MB

11. Milestone Project 1 Supervised Learning (Classification)/11. Choosing The Right Models.mp496.43MB

11. Milestone Project 1 Supervised Learning (Classification)/12. Experimenting With Machine Learning Models.mp455.35MB

11. Milestone Project 1 Supervised Learning (Classification)/13. TuningImproving Our Model.mp4102.78MB

11. Milestone Project 1 Supervised Learning (Classification)/14. Tuning Hyperparameters.mp4108.01MB

11. Milestone Project 1 Supervised Learning (Classification)/15. Tuning Hyperparameters 2.mp4104.12MB

11. Milestone Project 1 Supervised Learning (Classification)/16. Tuning Hyperparameters 3.mp463.02MB

11. Milestone Project 1 Supervised Learning (Classification)/17. Evaluating Our Model.mp471.6MB

11. Milestone Project 1 Supervised Learning (Classification)/18. Evaluating Our Model 2.mp441.54MB

11. Milestone Project 1 Supervised Learning (Classification)/19. Evaluating Our Model 3.mp464.84MB

11. Milestone Project 1 Supervised Learning (Classification)/2. Project Overview.mp434.45MB

11. Milestone Project 1 Supervised Learning (Classification)/20. Finding The Most Important Features.mp4127.49MB

11. Milestone Project 1 Supervised Learning (Classification)/21. Reviewing The Project.mp486.14MB

11. Milestone Project 1 Supervised Learning (Classification)/3. Project Environment Setup.mp4100.76MB

11. Milestone Project 1 Supervised Learning (Classification)/4. Step 1~4 Framework Setup.mp4105.51MB

11. Milestone Project 1 Supervised Learning (Classification)/5. Getting Our Tools Ready.mp479.37MB

11. Milestone Project 1 Supervised Learning (Classification)/6. Exploring Our Data.mp466.89MB

11. Milestone Project 1 Supervised Learning (Classification)/7. Finding Patterns.mp463.35MB

11. Milestone Project 1 Supervised Learning (Classification)/8. Finding Patterns 2.mp499.93MB

11. Milestone Project 1 Supervised Learning (Classification)/9. Finding Patterns 3.mp4137.87MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp48.96MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp466.92MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp455.53MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.mp482.68MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Custom Evaluation Function.mp4103.34MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/15. Reducing Data.mp493.48MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/16. RandomizedSearchCV.mp485.83MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Improving Hyperparameters.mp479.29MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Preproccessing Our Data.mp4139.3MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Making Predictions.mp479.22MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp432.95MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/20. Feature Importance.mp4142.31MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4101.28MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/4. Step 1~4 Framework Setup.mp485.69MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.mp4137.82MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp452.05MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.mp4159.14MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.mp4146.17MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4106.34MB

13. Data Engineering/1. Data Engineering Introduction.mp413.5MB

13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp410.1MB

13. Data Engineering/12. Apache Spark and Apache Flink.mp45.76MB

13. Data Engineering/13. Kafka and Stream Processing.mp419.25MB

13. Data Engineering/2. What Is Data.mp442.22MB

13. Data Engineering/3. What Is A Data Engineer.mp415.16MB

13. Data Engineering/4. What Is A Data Engineer 2.mp424.24MB

13. Data Engineering/5. What Is A Data Engineer 3.mp424.29MB

13. Data Engineering/6. What Is A Data Engineer 4.mp414.93MB

13. Data Engineering/7. Types Of Databases.mp432.56MB

13. Data Engineering/9. Optional OLTP Databases.mp479.68MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/1. Section Overview.mp412.2MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/10. Optional TensorFlow 2.0 Default Issue.mp428.1MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/11. Using A GPU.mp480.59MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/12. Optional GPU and Google Colab.mp445.88MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/13. Optional Reloading Colab Notebook.mp488.66MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/14. Loading Our Data Labels.mp4114.83MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/15. Preparing The Images.mp4133.89MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/16. Turning Data Labels Into Numbers.mp4107.47MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/17. Creating Our Own Validation Set.mp466.44MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/18. Preprocess Images.mp490.1MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/19. Preprocess Images 2.mp4105.08MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/2. Deep Learning and Unstructured Data.mp4102.04MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/20. Turning Data Into Batches.mp487.78MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/21. Turning Data Into Batches 2.mp4149.39MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/22. Visualizing Our Data.mp4121.99MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/23. Preparing Our Inputs and Outputs.mp450.08MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/25. Building A Deep Learning Model.mp4121.85MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/26. Building A Deep Learning Model 2.mp4105.91MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/27. Building A Deep Learning Model 3.mp4105.92MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/28. Building A Deep Learning Model 4.mp486.31MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/29. Summarizing Our Model.mp445.44MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/30. Evaluating Our Model.mp479.29MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/31. Preventing Overfitting.mp436.51MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/32. Training Your Deep Neural Network.mp4166.61MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/33. Evaluating Performance With TensorBoard.mp474.18MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/34. Make And Transform Predictions.mp4154.98MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/35. Transform Predictions To Text.mp4129.87MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/36. Visualizing Model Predictions.mp4119.31MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/37. Visualizing And Evaluate Model Predictions 2.mp4143.79MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/38. Visualizing And Evaluate Model Predictions 3.mp4113.21MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/39. Saving And Loading A Trained Model.mp4126.98MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/4. Setting Up Google Colab.mp474.24MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/40. Training Model On Full Dataset.mp4139.83MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/41. Making Predictions On Test Images.mp4140.84MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/42. Submitting Model to Kaggle.mp4121.35MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/43. Making Predictions On Our Images.mp4119.24MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/5. Google Colab Workspace.mp439.63MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/6. Uploading Project Data.mp451.99MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/7. Setting Up Our Data.mp442.26MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/8. Setting Up Our Data 2.mp420.87MB

14. Neural Networks Deep Learning, Transfer Learning and TensorFlow 2/9. Importing TensorFlow 2.mp4116.77MB

15. Storytelling + Communication How To Present Your Work/1. Section Overview.mp410.93MB

15. Storytelling + Communication How To Present Your Work/2. Communicating Your Work.mp420.2MB

15. Storytelling + Communication How To Present Your Work/3. Communicating With Managers.mp418.38MB

15. Storytelling + Communication How To Present Your Work/4. Communicating With Co-Workers.mp419MB

15. Storytelling + Communication How To Present Your Work/5. Weekend Project Principle.mp423.59MB

15. Storytelling + Communication How To Present Your Work/6. Communicating With Outside World.mp414.53MB

15. Storytelling + Communication How To Present Your Work/7. Storytelling.mp412.03MB

16. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4118.35MB

16. Career Advice + Extra Bits/11. Contributing To Open Source.mp4130.26MB

16. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4113.04MB

16. Career Advice + Extra Bits/3. What If I Don't Have Enough Experience.mp4160.94MB

16. Career Advice + Extra Bits/6. JTS Learn to Learn.mp411.15MB

16. Career Advice + Extra Bits/7. JTS Start With Why.mp415.44MB

16. Career Advice + Extra Bits/9. CWD Git + Github.mp4176.11MB

17. Learn Python/1. What Is A Programming Language.mp4104.78MB

17. Learn Python/10. Numbers.mp472.71MB

17. Learn Python/11. Math Functions.mp441.82MB

17. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp459.71MB

17. Learn Python/13. Operator Precedence.mp414.42MB

17. Learn Python/15. Optional bin() and complex.mp421.9MB

17. Learn Python/16. Variables.mp493.56MB

17. Learn Python/17. Expressions vs Statements.mp410.97MB

17. Learn Python/18. Augmented Assignment Operator.mp415.33MB

17. Learn Python/19. Strings.mp430.99MB

17. Learn Python/2. Python Interpreter.mp493.47MB

17. Learn Python/20. String Concatenation.mp47.34MB

17. Learn Python/21. Type Conversion.mp419MB

17. Learn Python/22. Escape Sequences.mp423.16MB

17. Learn Python/23. Formatted Strings.mp449.25MB

17. Learn Python/24. String Indexes.mp449.15MB

17. Learn Python/25. Immutability.mp420.8MB

17. Learn Python/26. Built-In Functions + Methods.mp469.4MB

17. Learn Python/27. Booleans.mp416.55MB

17. Learn Python/28. Exercise Type Conversion.mp450.34MB

17. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp429.25MB

17. Learn Python/3. How To Run Python Code.mp463.9MB

17. Learn Python/30. Exercise Password Checker.mp451.1MB

17. Learn Python/31. Lists.mp421.97MB

17. Learn Python/32. List Slicing.mp449.87MB

17. Learn Python/33. Matrix.mp419.16MB

17. Learn Python/34. List Methods.mp461.75MB

17. Learn Python/35. List Methods 2.mp427.4MB

17. Learn Python/36. List Methods 3.mp427.66MB

17. Learn Python/37. Common List Patterns.mp440.47MB

17. Learn Python/38. List Unpacking.mp413.87MB

17. Learn Python/39. None.mp47.93MB

17. Learn Python/4. Our First Python Program.mp447.21MB

17. Learn Python/40. Dictionaries.mp432.7MB

17. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp426.63MB

17. Learn Python/42. Dictionary Keys.mp420.38MB

17. Learn Python/43. Dictionary Methods.mp427.16MB

17. Learn Python/44. Dictionary Methods 2.mp442.4MB

17. Learn Python/45. Tuples.mp425.66MB

17. Learn Python/46. Tuples 2.mp416.99MB

17. Learn Python/47. Sets.mp436.99MB

17. Learn Python/48. Sets 2.mp464.27MB

17. Learn Python/5. Python 2 vs Python 3.mp482.15MB

17. Learn Python/6. Exercise How Does Python Work.mp425.96MB

17. Learn Python/7. Learning Python.mp438.53MB

17. Learn Python/8. Python Data Types.mp428.85MB

18. Learn Python Part 2/1. Breaking The Flow.mp420.34MB

18. Learn Python Part 2/10. For Loops.mp434.32MB

18. Learn Python Part 2/11. Iterables.mp443.2MB

18. Learn Python Part 2/12. Exercise Tricky Counter.mp416.39MB

18. Learn Python Part 2/13. range().mp428.32MB

18. Learn Python Part 2/14. enumerate().mp424.81MB

18. Learn Python Part 2/15. While Loops.mp428.32MB

18. Learn Python Part 2/16. While Loops 2.mp425.94MB

18. Learn Python Part 2/17. break, continue, pass.mp422.22MB

18. Learn Python Part 2/18. Our First GUI.mp449.64MB

18. Learn Python Part 2/19. DEVELOPER FUNDAMENTALS IV.mp450.22MB

18. Learn Python Part 2/2. Conditional Logic.mp474.58MB

18. Learn Python Part 2/20. Exercise Find Duplicates.mp420.26MB

18. Learn Python Part 2/21. Functions.mp448.6MB

18. Learn Python Part 2/22. Parameters and Arguments.mp423.15MB

18. Learn Python Part 2/23. Default Parameters and Keyword Arguments.mp438.15MB

18. Learn Python Part 2/24. return.mp463.04MB

18. Learn Python Part 2/26. Methods vs Functions.mp430.69MB

18. Learn Python Part 2/27. Docstrings.mp417.34MB

18. Learn Python Part 2/28. Clean Code.mp419.67MB

18. Learn Python Part 2/29. args and kwargs.mp443.02MB

18. Learn Python Part 2/3. Indentation In Python.mp428.03MB

18. Learn Python Part 2/30. Exercise Functions.mp421.86MB

18. Learn Python Part 2/31. Scope.mp420.14MB

18. Learn Python Part 2/32. Scope Rules.mp437.69MB

18. Learn Python Part 2/33. global Keyword.mp436.51MB

18. Learn Python Part 2/34. nonlocal Keyword.mp418.26MB

18. Learn Python Part 2/35. Why Do We Need Scope.mp419.18MB

18. Learn Python Part 2/36. Pure Functions.mp467.37MB

18. Learn Python Part 2/37. map().mp438.38MB

18. Learn Python Part 2/38. filter().mp423.56MB

18. Learn Python Part 2/39. zip().mp421.27MB

18. Learn Python Part 2/4. Truthy vs Falsey.mp442.82MB

18. Learn Python Part 2/40. reduce().mp452.27MB

18. Learn Python Part 2/41. List Comprehensions.mp453.34MB

18. Learn Python Part 2/42. Set Comprehensions.mp435.37MB

18. Learn Python Part 2/43. Exercise Comprehensions.mp421.97MB

18. Learn Python Part 2/45. Modules in Python.mp482.18MB

18. Learn Python Part 2/47. Optional PyCharm.mp453.06MB

18. Learn Python Part 2/48. Packages in Python.mp472.43MB

18. Learn Python Part 2/49. Different Ways To Import.mp447.97MB

18. Learn Python Part 2/5. Ternary Operator.mp419.71MB

18. Learn Python Part 2/6. Short Circuiting.mp419.39MB

18. Learn Python Part 2/7. Logical Operators.mp428.34MB

18. Learn Python Part 2/8. Exercise Logical Operators.mp446.62MB

18. Learn Python Part 2/9. is vs ==.mp433.57MB

2. Machine Learning 101/1. What Is Machine Learning.mp428.33MB

2. Machine Learning 101/2. AIMachine LearningData Science.mp419.67MB

2. Machine Learning 101/3. Exercise Machine Learning Playground.mp442.59MB

2. Machine Learning 101/4. How Did We Get Here.mp430.51MB

2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp419.43MB

2. Machine Learning 101/6. Types of Machine Learning.mp422.76MB

2. Machine Learning 101/8. What Is Machine Learning Round 2.mp425.52MB

2. Machine Learning 101/9. Section Review.mp45.56MB

20. Where To Go From Here/2. Thank You.mp411.12MB

3. Machine Learning and Data Science Framework/1. Section Overview.mp413.35MB

3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp415.99MB

3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp444.89MB

3. Machine Learning and Data Science Framework/13. Experimentation.mp421.33MB

3. Machine Learning and Data Science Framework/14. Tools We Will Use.mp427.34MB

3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp411.38MB

3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp423.47MB

3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.mp460.5MB

3. Machine Learning and Data Science Framework/5. Types of Data.mp429.33MB

3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp417.75MB

3. Machine Learning and Data Science Framework/7. Features In Data.mp436.78MB

3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp427.51MB

3. Machine Learning and Data Science Framework/9. Modelling - Picking the Model.mp423.25MB

4. The 2 Paths/1. The 2 Paths.mp49.75MB

5. Data Science Environment Setup/1. Section Overview.mp46.03MB

5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough.mp467.35MB

5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 2.mp4103.9MB

5. Data Science Environment Setup/13. Jupyter Notebook Walkthrough 3.mp471.42MB

5. Data Science Environment Setup/2. Introducing Our Tools.mp419.29MB

5. Data Science Environment Setup/3. What is Conda.mp412.48MB

5. Data Science Environment Setup/4. Conda Environments.mp430.57MB

5. Data Science Environment Setup/5. Mac Environment Setup.mp4144.4MB

5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4125.47MB

5. Data Science Environment Setup/7. Windows Environment Setup.mp447.92MB

5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4227.61MB

6. Pandas Data Analysis/1. Section Overview.mp410.87MB

6. Pandas Data Analysis/10. Manipulating Data 2.mp486.53MB

6. Pandas Data Analysis/11. Manipulating Data 3.mp491.02MB

6. Pandas Data Analysis/13. How To Download The Course Assignments.mp466.78MB

6. Pandas Data Analysis/3. Pandas Introduction.mp427.45MB

6. Pandas Data Analysis/4. Series, Data Frames and CSVs.mp495.37MB

6. Pandas Data Analysis/6. Describing Data with Pandas.mp475.56MB

6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.mp472.36MB

6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.mp4106.51MB

6. Pandas Data Analysis/9. Manipulating Data.mp4104.99MB

7. NumPy/1. Section Overview.mp413.33MB

7. NumPy/10. Standard Deviation and Variance.mp451.17MB

7. NumPy/11. Reshape and Transpose.mp453.53MB

7. NumPy/12. Dot Product vs Element Wise.mp483.94MB

7. NumPy/13. Exercise Nut Butter Store Sales.mp491.33MB

7. NumPy/14. Comparison Operators.mp426.38MB

7. NumPy/15. Sorting Arrays.mp432.83MB

7. NumPy/16. Turn Images Into NumPy Arrays.mp485.92MB

7. NumPy/2. NumPy Introduction.mp426.85MB

7. NumPy/4. NumPy DataTypes and Attributes.mp478.99MB

7. NumPy/5. Creating NumPy Arrays.mp466.78MB

7. NumPy/6. NumPy Random Seed.mp451.93MB

7. NumPy/7. Viewing Arrays and Matrices.mp470.65MB

7. NumPy/8. Manipulating Arrays.mp480.65MB

7. NumPy/9. Manipulating Arrays 2.mp467.91MB

8. Matplotlib Plotting and Data Visualization/1. Section Overview.mp48.6MB

8. Matplotlib Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp498.81MB

8. Matplotlib Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp474.72MB

8. Matplotlib Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp449MB

8. Matplotlib Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp456.96MB

8. Matplotlib Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp482.05MB

8. Matplotlib Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4119.76MB

8. Matplotlib Plotting and Data Visualization/17. Customizing Your Plots.mp492.22MB

8. Matplotlib Plotting and Data Visualization/18. Customizing Your Plots 2.mp4123.6MB

8. Matplotlib Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp449.52MB

8. Matplotlib Plotting and Data Visualization/2. Matplotlib Introduction.mp431.51MB

8. Matplotlib Plotting and Data Visualization/3. Importing And Using Matplotlib.mp486.46MB

8. Matplotlib Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp482.16MB

8. Matplotlib Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp467.04MB

8. Matplotlib Plotting and Data Visualization/6. Histograms And Subplots.mp469.75MB

8. Matplotlib Plotting and Data Visualization/7. Subplots Option 2.mp438.09MB

8. Matplotlib Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp412.25MB

8. Matplotlib Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp460.35MB

9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp412.47MB

9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp416.54MB

9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.mp4135.03MB

9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4104.85MB

9. Scikit-learn Creating Machine Learning Models/14. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4136.9MB

9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data.mp4143.27MB

9. Scikit-learn Creating Machine Learning Models/16. Choosing The Right Model For Your Data 2 (Regression).mp486.93MB

9. Scikit-learn Creating Machine Learning Models/18. Quick Tip How ML Algorithms Work.mp411.07MB

9. Scikit-learn Creating Machine Learning Models/19. Choosing The Right Model For Your Data 3 (Classification).mp4118.85MB

9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp440.63MB

9. Scikit-learn Creating Machine Learning Models/20. Fitting A Model To The Data.mp456.57MB

9. Scikit-learn Creating Machine Learning Models/21. Making Predictions With Our Model.mp466.5MB

9. Scikit-learn Creating Machine Learning Models/22. predict() vs predict_proba().mp454.33MB

9. Scikit-learn Creating Machine Learning Models/23. Making Predictions With Our Model (Regression).mp444.92MB

9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model (Score).mp487.14MB

9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Machine Learning Model 2 (Cross Validation).mp495.98MB

9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 1 (Accuracy).mp431.42MB

9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 2 (ROC Curve).mp466.04MB

9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 3 (ROC Curve).mp450.62MB

9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 4 (Confusion Matrix).mp477.72MB

9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 5 (Confusion Matrix).mp463.6MB

9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Classification Model 6 (Classification Report).mp487.25MB

9. Scikit-learn Creating Machine Learning Models/32. Evaluating A Regression Model 1 (R2 Score).mp470.4MB

9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 2 (MAE).mp428.52MB

9. Scikit-learn Creating Machine Learning Models/34. Evaluating A Regression Model 3 (MSE).mp454.91MB

9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Cross Validation and Scoring Parameter.mp491.5MB

9. Scikit-learn Creating Machine Learning Models/37. Evaluating A Model With Scikit-learn Functions.mp494.82MB

9. Scikit-learn Creating Machine Learning Models/38. Improving A Machine Learning Model.mp490.94MB

9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters.mp4175.57MB

9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp488.28MB

9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 2.mp4116.78MB

9. Scikit-learn Creating Machine Learning Models/41. Tuning Hyperparameters 3.mp4121.77MB

9. Scikit-learn Creating Machine Learning Models/42. Quick Tip Correlation Analysis.mp416.92MB

9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model.mp452.61MB

9. Scikit-learn Creating Machine Learning Models/44. Saving And Loading A Model 2.mp456.78MB

9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together.mp4158.36MB

9. Scikit-learn Creating Machine Learning Models/46. Putting It All Together 2.mp4116.86MB

9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp475.14MB

9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4190.19MB

9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4176.14MB

9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp463.67MB