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

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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
17. Career Advice + Extra Bits/9. CWD Git + Github.mp4 176.1 MB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4 175.5 MB
17. 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/44. Putting It All Together.mp4 158.4 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
9. Scikit-learn Creating Machine Learning Models/14. 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
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4 139.3 MB
11. Milestone Project 1 Supervised Learning (Binary 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/13. 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
17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4 130.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.mp4 127.5 MB
5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4 125.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4 123.7 MB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4 121.8 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4 119.8 MB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4 118.8 MB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4 118.4 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4 116.9 MB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4 116.8 MB
17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4 113.1 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4 108.0 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4 106.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4 105.5 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
18. Learn Python/1. What Is A Programming Language.mp4 104.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.mp4 104.1 MB
5. Data Science Environment Setup/11. 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 (Binary Classification)/13. TuningImproving Our Model.mp4 102.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4 101.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4 100.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp4 99.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4 98.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp4 96.4 MB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 96.0 MB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4 94.8 MB
18. Learn Python/16. Variables.mp4 93.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4 93.5 MB
18. Learn Python/2. Python Interpreter.mp4 93.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4 92.2 MB
9. Scikit-learn Creating Machine Learning Models/35. 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/37. Improving A Machine Learning Model.mp4 90.9 MB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4 88.3 MB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4 87.2 MB
9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4 87.1 MB
9. Scikit-learn Creating Machine Learning Models/15. 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 + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4 86.4 MB
11. Milestone Project 1 Supervised Learning (Binary 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
8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4 82.2 MB
18. Learn Python/5. Python 2 vs Python 3.mp4 82.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4 82.0 MB
7. NumPy/8. Manipulating Arrays.mp4 80.7 MB
13. Data Engineering/9. Optional OLTP Databases.mp4 79.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp4 79.4 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/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 77.7 MB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4 75.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4 74.7 MB
18. Learn Python/10. Numbers.mp4 72.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp4 72.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.mp4 71.6 MB
7. NumPy/7. Viewing Arrays and Matrices.mp4 70.6 MB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4 70.4 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4 69.7 MB
18. Learn Python/26. Built-In Functions + Methods.mp4 69.4 MB
7. NumPy/9. Manipulating Arrays 2.mp4 67.9 MB
5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4 67.3 MB
8. Matplotlib + Seaborn 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 (Binary 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/20. Making Predictions With Our Model.mp4 66.5 MB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4 66.0 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.mp4 64.8 MB
18. Learn Python/48. Sets 2.mp4 64.3 MB
18. 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/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 63.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp4 63.3 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp4 63.0 MB
18. 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 + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4 60.3 MB
18. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4 59.7 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4 57.0 MB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4 56.8 MB
9. Scikit-learn Creating Machine Learning Models/19. 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 (Binary Classification)/12. Experimenting With Machine Learning Models.mp4 55.3 MB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4 54.9 MB
9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4 54.3 MB
7. NumPy/11. Reshape and Transpose.mp4 53.5 MB
9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4 52.6 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.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
18. Learn Python/30. Exercise Password Checker.mp4 51.1 MB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4 50.6 MB
18. Learn Python/28. Exercise Type Conversion.mp4 50.3 MB
18. Learn Python/32. List Slicing.mp4 49.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4 49.5 MB
18. Learn Python/23. Formatted Strings.mp4 49.3 MB
18. Learn Python/24. String Indexes.mp4 49.2 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4 49.0 MB
5. Data Science Environment Setup/7. Windows Environment Setup.mp4 47.9 MB
18. Learn Python/4. Our First Python Program.mp4 47.2 MB
9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4 44.9 MB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4 44.9 MB
2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4 42.6 MB
18. Learn Python/44. Dictionary Methods 2.mp4 42.4 MB
13. Data Engineering/2. What Is Data.mp4 42.2 MB
18. Learn Python/11. Math Functions.mp4 41.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp4 41.5 MB
1. Introduction/1. Course Outline.mp4 40.7 MB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4 40.6 MB
18. Learn Python/37. Common List Patterns.mp4 40.5 MB
18. Learn Python/7. Learning Python.mp4 38.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4 38.1 MB
5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4 37.9 MB
18. Learn Python/47. Sets.mp4 37.0 MB
3. Machine Learning and Data Science Framework/7. Features In Data.mp4 36.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp4 34.4 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
18. Learn Python/40. Dictionaries.mp4 32.7 MB
13. Data Engineering/7. Types Of Databases.mp4 32.6 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4 31.5 MB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4 31.4 MB
18. Learn Python/19. Strings.mp4 31.0 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
18. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4 29.2 MB
18. Learn Python/8. Python Data Types.mp4 28.8 MB
18. 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
18. 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
18. Learn Python/43. Dictionary Methods.mp4 27.2 MB
7. NumPy/2. NumPy Introduction.mp4 26.8 MB
18. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4 26.6 MB
7. NumPy/14. Comparison Operators.mp4 26.4 MB
18. Learn Python/6. Exercise How Does Python Work.mp4 26.0 MB
18. Learn Python/45. Tuples.mp4 25.6 MB
2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4 25.5 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
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 23.2 MB
18. Learn Python/22. Escape Sequences.mp4 23.2 MB
2. Machine Learning 101/6. Types of Machine Learning.mp4 22.7 MB
19. Learn Python Part 2/43. Exercise Comprehensions.mp4 22.0 MB
18. Learn Python/31. Lists.mp4 22.0 MB
18. Learn Python/15. Optional bin() and complex.mp4 21.9 MB
19. 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/25. Immutability.mp4 20.8 MB
18. Learn Python/42. Dictionary Keys.mp4 20.4 MB
2. Machine Learning 101/2. AIMachine LearningData Science.mp4 19.7 MB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.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/33. Matrix.mp4 19.1 MB
18. Learn Python/21. Type Conversion.mp4 19.0 MB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4 17.8 MB
18. Learn Python/46. Tuples 2.mp4 17.0 MB
2. Machine Learning 101/1. What Is Machine Learning.mp4 16.9 MB
18. Learn Python/27. Booleans.mp4 16.5 MB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4 16.5 MB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4 16.0 MB
17. Career Advice + Extra Bits/7. JTS Start With Why.mp4 15.4 MB
18. 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
18. Learn Python/13. Operator Precedence.mp4 14.4 MB
18. 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 13.3 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 + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4 12.3 MB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4 11.4 MB
17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4 11.1 MB
21. Where To Go From Here/2. Thank You.mp4 11.1 MB
18. Learn Python/17. Expressions vs Statements.mp4 11.0 MB
6. Pandas Data Analysis/1. Section Overview.mp4 10.9 MB
11. Milestone Project 1 Supervised Learning (Binary 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 8.9 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4 8.6 MB
1. Introduction/4. Your First Day.mp4 8.2 MB
18. Learn Python/39. None.mp4 7.9 MB
18. Learn Python/20. String Concatenation.mp4 7.3 MB
7. NumPy/16.2 numpy-images.zip.zip 7.3 MB
13. Data Engineering/12. Apache Spark and Apache Flink.mp4 5.8 MB
2. Machine Learning 101/9. Section Review.mp4 2.5 MB
5. Data Science Environment Setup/1. Section Overview.mp4 2.3 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png 654.8 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png 369.4 KB
6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png 333.2 KB
6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png 333.2 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4.jpg 214.5 KB
5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.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
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt 30.5 KB
6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv 30.2 KB
9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt 26.4 KB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt 25.5 KB
5. Data Science Environment Setup/5. Mac Environment Setup.srt 23.9 KB
9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt 23.1 KB
9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt 22.7 KB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt 22.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.srt 22.3 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.srt 22.3 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt 22.3 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt 22.1 KB
9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt 21.4 KB
17. Career Advice + Extra Bits/9. CWD Git + Github.srt 21.2 KB
5. Data Science Environment Setup/6. Mac Environment Setup 2.srt 20.7 KB
17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.srt 20.0 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt 20.0 KB
7. NumPy/4. NumPy DataTypes and Attributes.srt 19.2 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.srt 18.9 KB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt 18.8 KB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.srt 18.2 KB
6. Pandas Data Analysis/9. Manipulating Data.srt 18.1 KB
9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt 18.0 KB
6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt 17.9 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt 17.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.srt 17.6 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt 17.3 KB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt 17.3 KB
17. Career Advice + Extra Bits/11. Contributing To Open Source.srt 17.1 KB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt 17.1 KB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt 17.0 KB
7. NumPy/13. Exercise Nut Butter Store Sales.srt 17.0 KB
9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt 16.9 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt 16.9 KB
6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt 16.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.srt 16.6 KB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.srt 16.3 KB
7. NumPy/8. Manipulating Arrays.srt 16.2 KB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.srt 16.1 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt 16.1 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.srt 16.0 KB
18. Learn Python/16. Variables.srt 16.0 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.srt 15.9 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.srt 15.7 KB
19. Learn Python Part 2/2. Conditional Logic.srt 15.7 KB
7. NumPy/12. Dot Product vs Element Wise.srt 15.3 KB
5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.srt 15.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.srt 15.1 KB
9. Scikit-learn Creating Machine Learning Models/28. Evaluating A Classification Model 4 (Confusion Matrix).srt 15.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.srt 15.1 KB
19. Learn Python Part 2/24. return.srt 15.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.srt 14.9 KB
9. Scikit-learn Creating Machine Learning Models/37. Improving A Machine Learning Model.srt 14.9 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/5. Scatter Plot And Bar Plot.srt 14.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.srt 14.6 KB
6. Pandas Data Analysis/7. Selecting and Viewing Data with Pandas.srt 14.6 KB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).srt 14.6 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.srt 14.4 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.srt 14.2 KB
3. Machine Learning and Data Science Framework/4. Types of Machine Learning Problems.srt 14.0 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.srt 14.0 KB
6. Pandas Data Analysis/10. Manipulating Data 2.srt 13.8 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/21. Reviewing The Project.srt 13.8 KB
6. Pandas Data Analysis/11. Manipulating Data 3.srt 13.7 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.srt 13.6 KB
6. Pandas Data Analysis/6. Describing Data with Pandas.srt 13.6 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/12. Splitting Data.srt 13.5 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.srt 13.4 KB
8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.srt 13.3 KB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.srt 13.1 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.srt 13.0 KB
7. NumPy/7. Viewing Arrays and Matrices.srt 12.9 KB
9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).srt 12.9 KB
11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.srt 12.8 KB
19. Learn Python Part 2/45. Modules in Python.srt 12.7 KB
12. Milestone Project 2 Supervised Learning (Time Series Data)/15. RandomizedSearchCV.srt 12.7 KB
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