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文档列表
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
17. Career Advice + Extra Bits/9. CWD Git + Github.mp4
184.7 MB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4
184.1 MB
17. 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/44. Putting It All Together.mp4
166.0 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
9. Scikit-learn Creating Machine Learning Models/14. 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
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.mp4
146.1 MB
11. Milestone Project 1 Supervised Learning (Binary 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/13. 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
17. Career Advice + Extra Bits/11. Contributing To Open Source.mp4
136.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.mp4
133.7 MB
5. Data Science Environment Setup/6. Mac Environment Setup 2.mp4
131.6 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/18. Customizing Your Plots 2.mp4
129.7 MB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.mp4
127.7 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/16. Plotting from Pandas DataFrames 7.mp4
125.6 MB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).mp4
124.6 MB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.mp4
124.1 MB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.mp4
122.5 MB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.mp4
122.4 MB
17. Career Advice + Extra Bits/12. Contributing To Open Source 2.mp4
118.5 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/14. Tuning Hyperparameters.mp4
113.2 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.mp4
111.5 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.mp4
110.6 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
18. Learn Python/1. What Is A Programming Language.mp4
109.9 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/15. Tuning Hyperparameters 2.mp4
109.2 MB
5. Data Science Environment Setup/11. 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 (Binary Classification)/13. TuningImproving Our Model.mp4
107.8 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/3. Project Environment Setup.mp4
106.2 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4
105.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.mp4
104.8 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/11. Plotting From Pandas DataFrames 2.mp4
103.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/11. Choosing The Right Models.mp4
101.1 MB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4
100.6 MB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.mp4
99.4 MB
18. Learn Python/16. Variables.mp4
98.1 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/14. Reducing Data.mp4
98.0 MB
18. Learn Python/2. Python Interpreter.mp4
98.0 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/17. Customizing Your Plots.mp4
96.7 MB
9. Scikit-learn Creating Machine Learning Models/35. 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/37. Improving A Machine Learning Model.mp4
95.4 MB
9. Scikit-learn Creating Machine Learning Models/4. Refresher What Is Machine Learning.mp4
92.6 MB
9. Scikit-learn Creating Machine Learning Models/30. Evaluating A Classification Model 6 (Classification Report).mp4
91.5 MB
9. Scikit-learn Creating Machine Learning Models/23. Evaluating A Machine Learning Model (Score).mp4
91.4 MB
9. Scikit-learn Creating Machine Learning Models/15. 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 + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.mp4
90.6 MB
11. Milestone Project 1 Supervised Learning (Binary 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
8. Matplotlib + Seaborn Plotting and Data Visualization/4. Anatomy Of A Matplotlib Figure.mp4
86.1 MB
18. Learn Python/5. Python 2 vs Python 3.mp4
86.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/15. Plotting from Pandas DataFrames 6.mp4
86.0 MB
7. NumPy/8. Manipulating Arrays.mp4
84.6 MB
13. Data Engineering/9. Optional OLTP Databases.mp4
83.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/5. Getting Our Tools Ready.mp4
83.2 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/28. Evaluating A Classification Model 4 (Confusion Matrix).mp4
81.5 MB
9. Scikit-learn Creating Machine Learning Models/6. Scikit-learn Cheatsheet.mp4
78.8 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/12. Plotting from Pandas DataFrames 3.mp4
78.3 MB
18. Learn Python/10. Numbers.mp4
76.2 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/10. Preparing Our Data For Machine Learning.mp4
76.1 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/17. Evaluating Our Model.mp4
75.1 MB
7. NumPy/7. Viewing Arrays and Matrices.mp4
74.1 MB
9. Scikit-learn Creating Machine Learning Models/31. Evaluating A Regression Model 1 (R2 Score).mp4
73.8 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/6. Histograms And Subplots.mp4
73.1 MB
18. Learn Python/26. Built-In Functions + Methods.mp4
72.8 MB
7. NumPy/9. Manipulating Arrays 2.mp4
71.2 MB
5. Data Science Environment Setup/10. Jupyter Notebook Walkthrough.mp4
70.6 MB
8. Matplotlib + Seaborn 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 (Binary 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/20. Making Predictions With Our Model.mp4
69.7 MB
9. Scikit-learn Creating Machine Learning Models/26. Evaluating A Classification Model 2 (ROC Curve).mp4
69.2 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/19. Evaluating Our Model 3.mp4
68.0 MB
18. Learn Python/48. Sets 2.mp4
67.4 MB
18. 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/29. Evaluating A Classification Model 5 (Confusion Matrix).mp4
66.7 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/7. Finding Patterns.mp4
66.4 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/16. Tuning Hyperparameters 3.mp4
66.1 MB
18. 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 + Seaborn Plotting and Data Visualization/9. Plotting From Pandas DataFrames.mp4
63.3 MB
18. Learn Python/12. DEVELOPER FUNDAMENTALS I.mp4
62.6 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/14. Plotting from Pandas DataFrames 5.mp4
59.7 MB
9. Scikit-learn Creating Machine Learning Models/43. Saving And Loading A Model 2.mp4
59.5 MB
9. Scikit-learn Creating Machine Learning Models/19. 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 (Binary Classification)/12. Experimenting With Machine Learning Models.mp4
58.0 MB
9. Scikit-learn Creating Machine Learning Models/33. Evaluating A Regression Model 3 (MSE).mp4
57.6 MB
9. Scikit-learn Creating Machine Learning Models/21. predict() vs predict_proba().mp4
57.0 MB
7. NumPy/11. Reshape and Transpose.mp4
56.1 MB
9. Scikit-learn Creating Machine Learning Models/42. Saving And Loading A Model.mp4
55.2 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/6. Exploring Our Data 2.mp4
54.6 MB
7. NumPy/6. NumPy Random Seed.mp4
54.4 MB
7. NumPy/10. Standard Deviation and Variance.mp4
53.6 MB
18. Learn Python/30. Exercise Password Checker.mp4
53.6 MB
9. Scikit-learn Creating Machine Learning Models/27. Evaluating A Classification Model 3 (ROC Curve).mp4
53.1 MB
18. Learn Python/28. Exercise Type Conversion.mp4
52.8 MB
18. Learn Python/32. List Slicing.mp4
52.3 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/19. Saving And Sharing Your Plots.mp4
51.9 MB
18. Learn Python/23. Formatted Strings.mp4
51.7 MB
18. Learn Python/24. String Indexes.mp4
51.5 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/13. Plotting from Pandas DataFrames 4.mp4
51.4 MB
5. Data Science Environment Setup/7. Windows Environment Setup.mp4
50.2 MB
18. Learn Python/4. Our First Python Program.mp4
49.5 MB
9. Scikit-learn Creating Machine Learning Models/22. Making Predictions With Our Model (Regression).mp4
47.1 MB
3. Machine Learning and Data Science Framework/11. Modelling - Comparison.mp4
47.1 MB
2. Machine Learning 101/3. Exercise Machine Learning Playground.mp4
44.7 MB
18. Learn Python/44. Dictionary Methods 2.mp4
44.4 MB
13. Data Engineering/2. What Is Data.mp4
44.3 MB
18. Learn Python/11. Math Functions.mp4
43.8 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/18. Evaluating Our Model 2.mp4
43.6 MB
1. Introduction/1. Course Outline.mp4
42.7 MB
9. Scikit-learn Creating Machine Learning Models/2. Scikit-learn Introduction.mp4
42.6 MB
18. Learn Python/37. Common List Patterns.mp4
42.4 MB
18. Learn Python/7. Learning Python.mp4
40.4 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/7. Subplots Option 2.mp4
39.9 MB
5. Data Science Environment Setup/12. Jupyter Notebook Walkthrough 3.mp4
39.8 MB
18. Learn Python/47. Sets.mp4
38.8 MB
3. Machine Learning and Data Science Framework/7. Features In Data.mp4
38.6 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/2. Project Overview.mp4
36.1 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
18. Learn Python/40. Dictionaries.mp4
34.3 MB
13. Data Engineering/7. Types Of Databases.mp4
34.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/2. Matplotlib Introduction.mp4
33.0 MB
9. Scikit-learn Creating Machine Learning Models/25. Evaluating A Classification Model 1 (Accuracy).mp4
32.9 MB
18. Learn Python/19. Strings.mp4
32.5 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
30.8 MB
18. Learn Python/29. DEVELOPER FUNDAMENTALS II.mp4
30.7 MB
18. Learn Python/8. Python Data Types.mp4
30.3 MB
18. Learn Python/36. List Methods 3.mp4
29.0 MB
3. Machine Learning and Data Science Framework/8. Modelling - Splitting Data.mp4
28.8 MB
6. Pandas Data Analysis/3. Pandas Introduction.mp4
28.8 MB
18. 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
18. Learn Python/43. Dictionary Methods.mp4
28.5 MB
7. NumPy/2. NumPy Introduction.mp4
28.1 MB
18. Learn Python/41. DEVELOPER FUNDAMENTALS III.mp4
27.9 MB
7. NumPy/14. Comparison Operators.mp4
27.6 MB
18. Learn Python/6. Exercise How Does Python Work.mp4
27.2 MB
18. Learn Python/45. Tuples.mp4
26.9 MB
2. Machine Learning 101/8. What Is Machine Learning Round 2.mp4
26.8 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
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
18. Learn Python/22. Escape Sequences.mp4
24.3 MB
2. Machine Learning 101/6. Types of Machine Learning.mp4
23.9 MB
19. Learn Python Part 2/43. Exercise Comprehensions.mp4
23.0 MB
18. Learn Python/31. Lists.mp4
23.0 MB
18. Learn Python/15. Optional bin() and complex.mp4
23.0 MB
19. 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/25. Immutability.mp4
21.8 MB
18. Learn Python/42. Dictionary Keys.mp4
21.4 MB
2. Machine Learning 101/2. AIMachine LearningData Science.mp4
20.6 MB
2. Machine Learning 101/5. Exercise YouTube Recommendation Engine.mp4
20.4 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/33. Matrix.mp4
20.1 MB
18. Learn Python/21. Type Conversion.mp4
19.9 MB
3. Machine Learning and Data Science Framework/6. Types of Evaluation.mp4
18.6 MB
18. Learn Python/46. Tuples 2.mp4
17.8 MB
2. Machine Learning 101/1. What Is Machine Learning.mp4
17.7 MB
18. Learn Python/27. Booleans.mp4
17.4 MB
9. Scikit-learn Creating Machine Learning Models/10. Quick Tip Clean, Transform, Reduce.mp4
17.3 MB
3. Machine Learning and Data Science Framework/10. Modelling - Tuning.mp4
16.8 MB
17. Career Advice + Extra Bits/7. JTS Start With Why.mp4
16.2 MB
18. Learn Python/18. Augmented Assignment Operator.mp4
16.1 MB
13. Data Engineering/3. What Is A Data Engineer.mp4
15.9 MB
13. Data Engineering/6. What Is A Data Engineer 4.mp4
15.7 MB
18. Learn Python/13. Operator Precedence.mp4
15.1 MB
18. Learn Python/38. List Unpacking.mp4
14.5 MB
13. Data Engineering/1. Data Engineering Introduction.mp4
14.2 MB
3. Machine Learning and Data Science Framework/1. Section Overview.mp4
14.0 MB
7. NumPy/1. Section Overview.mp4
14.0 MB
5. Data Science Environment Setup/3. What is Conda.mp4
13.1 MB
9. Scikit-learn Creating Machine Learning Models/1. Section Overview.mp4
13.1 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/8. Quick Tip Data Visualizations.mp4
12.8 MB
3. Machine Learning and Data Science Framework/2. Introducing Our Framework.mp4
11.9 MB
17. Career Advice + Extra Bits/6. JTS Learn to Learn.mp4
11.7 MB
21. Where To Go From Here/2. Thank You.mp4
11.7 MB
18. Learn Python/17. Expressions vs Statements.mp4
11.5 MB
6. Pandas Data Analysis/1. Section Overview.mp4
11.4 MB
11. Milestone Project 1 Supervised Learning (Binary Classification)/1. Section Overview.mp4
10.7 MB
13. Data Engineering/11. Hadoop, HDFS and MapReduce.mp4
10.6 MB
4. The 2 Paths/1. The 2 Paths.mp4
10.2 MB
12. Milestone Project 2 Supervised Learning (Time Series Data)/1. Section Overview.mp4
9.4 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/1. Section Overview.mp4
9.0 MB
1. Introduction/4. Your First Day.mp4
8.6 MB
18. Learn Python/39. None.mp4
8.3 MB
18. Learn Python/20. String Concatenation.mp4
7.7 MB
7. NumPy/16.2 numpy-images.zip.zip
7.6 MB
13. Data Engineering/12. Apache Spark and Apache Flink.mp4
6.0 MB
2. Machine Learning 101/9. Section Review.mp4
2.6 MB
5. Data Science Environment Setup/1. Section Overview.mp4
2.4 MB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.2 matplotlib-anatomy-of-a-plot-with-code.png.png
670.5 kB
8. Matplotlib + Seaborn Plotting and Data Visualization/4.1 matplotlib-anatomy-of-a-plot.png.png
378.3 kB
6. Pandas Data Analysis/10.1 pandas-anatomy-of-a-dataframe.png.png
341.2 kB
6. Pandas Data Analysis/4.1 pandas-anatomy-of-a-dataframe.png.png
341.2 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/3. Project Environment Setup.mp4.jpg
219.7 kB
5. Data Science Environment Setup/3.4 conda-cheatsheet.pdf.pdf
206.1 kB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.srt
32.5 kB
5. Data Science Environment Setup/8. Windows Environment Setup 2.srt
32.4 kB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.srt
31.3 kB
6. Pandas Data Analysis/9.1 car-sales-extended-missing-data.csv.csv
30.9 kB
9. Scikit-learn Creating Machine Learning Models/44. Putting It All Together.srt
27.1 kB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.srt
26.1 kB
5. Data Science Environment Setup/5. Mac Environment Setup.srt
24.5 kB
9. Scikit-learn Creating Machine Learning Models/13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt
23.7 kB
9. Scikit-learn Creating Machine Learning Models/11. Getting Your Data Ready Convert Data To Numbers.srt
23.3 kB
5. Data Science Environment Setup/11. Jupyter Notebook Walkthrough 2.srt
23.0 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/20. Finding The Most Important Features.srt
22.9 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/8. Finding Patterns 2.srt
22.9 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/8. Turning Data Into Numbers.srt
22.9 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/7. Feature Engineering.srt
22.7 kB
9. Scikit-learn Creating Machine Learning Models/14. Choosing The Right Model For Your Data.srt
21.9 kB
17. Career Advice + Extra Bits/9. CWD Git + Github.srt
21.7 kB
5. Data Science Environment Setup/6. Mac Environment Setup 2.srt
21.2 kB
17. Career Advice + Extra Bits/3. What If I Don_t Have Enough Experience.srt
20.5 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/5. Exploring Our Data.srt
20.5 kB
7. NumPy/4. NumPy DataTypes and Attributes.srt
19.7 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/9. Finding Patterns 3.srt
19.3 kB
9. Scikit-learn Creating Machine Learning Models/40. Tuning Hyperparameters 3.srt
19.2 kB
17. Career Advice + Extra Bits/10. CWD Git + Github 2.srt
18.7 kB
6. Pandas Data Analysis/9. Manipulating Data.srt
18.5 kB
9. Scikit-learn Creating Machine Learning Models/35. Evaluating A Model With Cross Validation and Scoring Parameter.srt
18.4 kB
6. Pandas Data Analysis/8. Selecting and Viewing Data with Pandas Part 2.srt
18.4 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/17. Preproccessing Our Data.srt
18.2 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/13. TuningImproving Our Model.srt
18.1 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/19. Feature Importance.srt
17.7 kB
9. Scikit-learn Creating Machine Learning Models/24. Evaluating A Machine Learning Model 2 (Cross Validation).srt
17.7 kB
17. Career Advice + Extra Bits/11. Contributing To Open Source.srt
17.5 kB
9. Scikit-learn Creating Machine Learning Models/18. Choosing The Right Model For Your Data 3 (Classification).srt
17.5 kB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters 2.srt
17.4 kB
7. NumPy/13. Exercise Nut Butter Store Sales.srt
17.4 kB
9. Scikit-learn Creating Machine Learning Models/12. Getting Your Data Ready Handling Missing Values With Pandas.srt
17.4 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/9. Filling Missing Numerical Values.srt
17.3 kB
6. Pandas Data Analysis/4. Series, Data Frames and CSVs.srt
17.2 kB
11. Milestone Project 1 Supervised Learning (Binary Classification)/4. Step 1~4 Framework Setup.srt
17.0 kB
9. Scikit-learn Creating Machine Learning Models/36. Evaluating A Model With Scikit-learn Functions.srt
16.7 kB
7. NumPy/8. Manipulating Arrays.srt
16.6 kB
9. Scikit-learn Creating Machine Learning Models/45. Putting It All Together 2.srt
16.5 kB
12. Milestone Project 2 Supervised Learning (Time Series Data)/13. Custom Evaluation Function.srt
16.5 kB
8. Matplotlib + Seaborn Plotting and Data Visualization/3. Importing And Using Matplotlib.srt
16.4 kB
18. Learn Python/16. Variables.srt
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