种子简介

种子名称： GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery
文件类型： 视频
文件数目： 219个文件
文件大小： 13.24 GB
收录时间： 2022-10-14 18:10
已经下载： 3次
资源热度： 152
最近下载： 2024-6-16 13:46

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:efb3aa528657ed39712bf4d25f94593b1eb872dc&dn=GetFreeCourses.Me-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

GetFreeCourses.Me-Udemy-Complete Machine Learning and Data Science Zero to Mastery.torrent

1. Introduction/1. Course Outline.mp440.73MB

1. Introduction/4. Your First Day.mp48.24MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.mp410.19MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp472.6MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp496.42MB

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

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

11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4108MB

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

11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp463.01MB

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

11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp441.53MB

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

11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp434.44MB

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

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

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

11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4105.5MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp479.36MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/6. Exploring Our Data.mp466.88MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp463.34MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp499.92MB

11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.mp4137.86MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp48.95MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/10. Filling Missing Categorical Values.mp466.91MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/11. Fitting A Machine Learning Model.mp455.52MB

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

12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.mp4103.34MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp493.47MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.mp485.83MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/16. Improving Hyperparameters.mp479.29MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4139.3MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/18. Making Predictions.mp479.21MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.mp4142.3MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/2. Project Overview.mp432.94MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4101.27MB

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.mp4137.81MB

12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp452.04MB

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.mp410.11MB

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.mp432.55MB

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

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

17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4130.25MB

17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4113.05MB

17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.mp4160.95MB

17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp411.14MB

17. Career Advice + Extra Bits/7. JTS Start With Why.mp415.43MB

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

18. Learn Python/1. What Is A Programming Language.mp4104.77MB

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

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

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

18. Learn Python/13. Operator Precedence.mp414.43MB

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

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

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

18. Learn Python/18. Augmented Assignment Operator.mp415.32MB

18. Learn Python/19. Strings.mp430.98MB

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

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

18. Learn Python/21. Type Conversion.mp418.99MB

18. Learn Python/22. Escape Sequences.mp423.15MB

18. Learn Python/23. Formatted Strings.mp449.26MB

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

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

18. Learn Python/26. Built-In Functions + Methods.mp469.39MB

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

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

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

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

18. Learn Python/30. Exercise Password Checker.mp451.09MB

18. Learn Python/31. Lists.mp421.96MB

18. Learn Python/32. List Slicing.mp449.86MB

18. Learn Python/33. Matrix.mp419.15MB

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

18. Learn Python/35. List Methods 2.mp427.41MB

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

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

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

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

18. Learn Python/4. Our First Python Program.mp447.2MB

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

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

18. Learn Python/42. Dictionary Keys.mp420.37MB

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

18. Learn Python/44. Dictionary Methods 2.mp442.39MB

18. Learn Python/45. Tuples.mp425.65MB

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

18. Learn Python/47. Sets.mp436.98MB

18. Learn Python/48. Sets 2.mp464.26MB

18. Learn Python/5. Python 2 vs Python 3.mp482.14MB

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

18. Learn Python/7. Learning Python.mp438.52MB

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

19. Learn Python Part 2/30. Exercise Functions.mp421.85MB

19. Learn Python Part 2/43. Exercise Comprehensions.mp421.96MB

2. Machine Learning 101/1. What Is Machine Learning.mp416.92MB

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

2. Machine Learning 101/3. Exercise Machine Learning Playground.mp442.6MB

2. Machine Learning 101/4. How Did We Get Here.mp430.5MB

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

2. Machine Learning 101/6. Types of Machine Learning.mp422.75MB

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

2. Machine Learning 101/9. Section Review.mp42.52MB

21. 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.mp415.98MB

3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp444.88MB

3. Machine Learning and Data Science Framework/12. Experimentation.mp421.33MB

3. Machine Learning and Data Science Framework/13. Tools We Will Use.mp427.33MB

3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp411.39MB

3. Machine Learning and Data Science Framework/3. 6 Step Machine Learning Framework.mp423.46MB

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.mp417.76MB

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.mp423.24MB

4. The 2 Paths/1. The 2 Paths.mp49.76MB

5. Data Science Environment Setup/1. Section Overview.mp42.27MB

5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp467.35MB

5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.mp4103.9MB

5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp437.94MB

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

5. Data Science Environment Setup/3. What is Conda.mp412.49MB

5. Data Science Environment Setup/4. Conda Environments.mp430.56MB

5. Data Science Environment Setup/5. Mac Environment Setup.mp4144.39MB

5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4125.46MB

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

5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4227.6MB

6. Pandas Data Analysis/1. Section Overview.mp410.88MB

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.mp427.44MB

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

7. NumPy/1. Section Overview.mp413.32MB

7. NumPy/10. Standard Deviation and Variance.mp451.16MB

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

7. NumPy/12. Dot Product vs Element Wise.mp483.93MB

7. NumPy/13. Exercise Nut Butter Store Sales.mp491.32MB

7. NumPy/14. Comparison Operators.mp426.37MB

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

7. NumPy/16. Turn Images Into NumPy Arrays.mp485.91MB

7. NumPy/2. NumPy Introduction.mp426.84MB

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

7. NumPy/5. Creating NumPy Arrays.mp466.77MB

7. NumPy/6. NumPy Random Seed.mp451.92MB

7. NumPy/7. Viewing Arrays and Matrices.mp470.64MB

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

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

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

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

8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp474.71MB

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

8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp456.97MB

8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp482.04MB

8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4119.75MB

8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp492.21MB

8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4123.66MB

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

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

8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp486.45MB

8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp482.15MB

8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.mp467.03MB

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

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

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

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

9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp412.46MB

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.mp4135.02MB

9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.mp4104.84MB

9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4136.89MB

9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.mp4143.26MB

9. Scikit-learn Creating Machine Learning Models/15. Choosing The Right Model For Your Data 2 (Regression).mp486.92MB

9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4118.84MB

9. Scikit-learn Creating Machine Learning Models/19. Fitting A Model To The Data.mp456.56MB

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

9. Scikit-learn Creating Machine Learning Models/20. Making Predictions With Our Model.mp466.5MB

9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp454.33MB

9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp444.91MB

9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp487.13MB

9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp495.97MB

9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp431.41MB

9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp466.03MB

9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp450.61MB

9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).mp477.72MB

9. Scikit-learn Creating Machine Learning Models/29. Evaluating A Classification Model 5 (Confusion Matrix).mp463.59MB

9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp487.24MB

9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp470.39MB

9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp454.9MB

9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.mp491.49MB

9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp494.82MB

9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.mp490.93MB

9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4175.53MB

9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4116.77MB

9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp488.27MB

9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4121.76MB

9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp452.6MB

9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp456.77MB

9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.mp4158.35MB

9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4116.85MB

9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp475.13MB

9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4190.18MB

9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4176.13MB

9. Scikit-learn Creating Machine Learning Models/9. Getting Your Data Ready Splitting Your Data.mp463.66MB