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| 1. Congratulations! You Are Now An ML Product Manager.mp4 |
5.54Мб |
| 1. Congratulations! You Are Now An ML Product Manager.srt |
3.07Кб |
| 1. Data Acquisition Strategies.mp4 |
42.66Мб |
| 1. Data Acquisition Strategies.srt |
14.18Кб |
| 1. Data Scrubbing.mp4 |
15.34Мб |
| 1. Data Scrubbing.srt |
9.59Кб |
| 1. How the ML PM's Role Differs.mp4 |
8.55Мб |
| 1. How the ML PM's Role Differs.srt |
4.13Кб |
| 1. The AI Flywheel.mp4 |
26.18Мб |
| 1. The AI Flywheel.srt |
5.86Кб |
| 1. The Confusion Matrix.mp4 |
32.26Мб |
| 1. The Confusion Matrix.srt |
5.99Кб |
| 1. Which ML algorithm should I use.mp4 |
6.24Мб |
| 1. Which ML algorithm should I use.srt |
3.31Кб |
| 10. Deep Learning.mp4 |
34.66Мб |
| 10. Deep Learning.srt |
9.74Кб |
| 11. ML Real World Examples.mp4 |
34.46Мб |
| 11. ML Real World Examples.srt |
6.16Кб |
| 12. ML Terminology.mp4 |
12.09Мб |
| 12. ML Terminology.srt |
4.46Кб |
| 13. Exercise #3 Apply your ML Lingo.mp4 |
40.42Мб |
| 13. Exercise #3 Apply your ML Lingo.srt |
9.09Кб |
| 14. Quiz #1 ML Introduction.html |
188б |
| 2.1 IBM Watson Failure.html |
148б |
| 2.2 Racial Bias In Facial Recognition Tools.html |
170б |
| 2. Build, Outsource or Buy Your ML Solution.mp4 |
12.99Мб |
| 2. Build, Outsource or Buy Your ML Solution.srt |
6.31Кб |
| 2. Evaluation Metrics (Precision, Recall & F1 Score).mp4 |
51.75Мб |
| 2. Evaluation Metrics (Precision, Recall & F1 Score).srt |
9.75Кб |
| 2. Google reCAPTCHA.mp4 |
50.50Мб |
| 2. Google reCAPTCHA.srt |
5.97Кб |
| 2. ML Product Horror Stories.mp4 |
65.50Мб |
| 2. ML Product Horror Stories.srt |
8.04Кб |
| 2. Organizing ML Teams.mp4 |
27.29Мб |
| 2. Organizing ML Teams.srt |
7.34Кб |
| 2. Sampling and Splitting Data.mp4 |
16.62Мб |
| 2. Sampling and Splitting Data.srt |
6.59Кб |
| 2. What is Machine Learning (ML).mp4 |
18.17Мб |
| 2. What is Machine Learning (ML).srt |
5.99Кб |
| 3. Adjusting Course Speed.html |
570б |
| 3. Exercise #12 Lets Calculate Evaluation Metrics.mp4 |
18.52Мб |
| 3. Exercise #12 Lets Calculate Evaluation Metrics.srt |
9.24Кб |
| 3. Exercise #9 Find Examples of User-Generated Data Labelling.mp4 |
23.78Мб |
| 3. Exercise #9 Find Examples of User-Generated Data Labelling.srt |
4.63Кб |
| 3. Key Roles in An ML Team.mp4 |
24.37Мб |
| 3. Key Roles in An ML Team.srt |
10.03Кб |
| 3. Machine Learning as a Service (MLaaS).mp4 |
76.79Мб |
| 3. Machine Learning as a Service (MLaaS).srt |
10.34Кб |
| 3. Transforming Data.mp4 |
13.26Мб |
| 3. Transforming Data.srt |
7.91Кб |
| 3. When to ML.mp4 |
13.76Мб |
| 3. When to ML.srt |
5.37Кб |
| 4. Feature Engineering.mp4 |
6.23Мб |
| 4. Feature Engineering.srt |
3.61Кб |
| 4. ML is Going Mainstream.mp4 |
50.74Мб |
| 4. ML is Going Mainstream.srt |
10.87Кб |
| 4. Regression (Linear, Polynomial, Logistic).mp4 |
10.69Мб |
| 4. Regression (Linear, Polynomial, Logistic).srt |
7.36Кб |
| 4. Start with a Simplified Problem.mp4 |
7.81Мб |
| 4. Start with a Simplified Problem.srt |
3.28Кб |
| 4. The ML Life Cycle.mp4 |
51.57Мб |
| 4. The ML Life Cycle.srt |
21.23Кб |
| 4. User Experience Optimization.mp4 |
20.31Мб |
| 4. User Experience Optimization.srt |
8.56Кб |
| 4. When not to ML.mp4 |
9.00Мб |
| 4. When not to ML.srt |
4.77Кб |
| 5.1 Right to Explanation.html |
111б |
| 5. Classification (SVM, K-NN, Decision Trees).mp4 |
27.67Мб |
| 5. Classification (SVM, K-NN, Decision Trees).srt |
13.97Кб |
| 5. Exercise #10 Design Your Data for The Model.mp4 |
14.53Мб |
| 5. Exercise #10 Design Your Data for The Model.srt |
4.41Кб |
| 5. Exercise #11 Brainstorm a new feature.mp4 |
16.81Мб |
| 5. Exercise #11 Brainstorm a new feature.srt |
5.28Кб |
| 5. Exercise #13 Precision, Recall or F1 score.mp4 |
24.98Мб |
| 5. Exercise #13 Precision, Recall or F1 score.srt |
8.44Кб |
| 5. Exercise #4 Need interpretability.mp4 |
36.75Мб |
| 5. Exercise #4 Need interpretability.srt |
9.40Кб |
| 5. Exercise#6 Create & Test Your Hypothesis.mp4 |
48.20Мб |
| 5. Exercise#6 Create & Test Your Hypothesis.srt |
12.18Кб |
| 5. Get Your Course Workbook.html |
655б |
| 6. Clustering (K-Means, Means Shift).mp4 |
17.04Мб |
| 6. Clustering (K-Means, Means Shift).srt |
8.36Кб |
| 6. Deployment Methods.mp4 |
18.40Мб |
| 6. Deployment Methods.srt |
8.40Кб |
| 6. Exercise #1 Pick Your Product.mp4 |
25.10Мб |
| 6. Exercise #1 Pick Your Product.srt |
6.49Кб |
| 6. Exercise #7 Frame Your ML Problem.mp4 |
16.51Мб |
| 6. Exercise #7 Frame Your ML Problem.srt |
5.19Кб |
| 6. ML Data Considerations.mp4 |
8.30Мб |
| 6. ML Data Considerations.srt |
3.91Кб |
| 6. Quiz #5 Prepare Your Data.html |
188б |
| 6. Top Open Data Sources.mp4 |
68.15Мб |
| 6. Top Open Data Sources.srt |
7.15Кб |
| 7. Anomaly Detection (Local Outlier Factor, DBSCAN).mp4 |
14.18Мб |
| 7. Anomaly Detection (Local Outlier Factor, DBSCAN).srt |
7.07Кб |
| 7. Exercise #5 To ML or Not to ML.mp4 |
75.08Мб |
| 7. Exercise #5 To ML or Not to ML.srt |
17.42Кб |
| 7. Exercise #8 Formulate Your ML Problem.mp4 |
26.42Мб |
| 7. Exercise #8 Formulate Your ML Problem.srt |
6.27Кб |
| 7. How Much Data Do I Need.mp4 |
10.61Мб |
| 7. How Much Data Do I Need.srt |
6.47Кб |
| 7. Monitoring Your Model.mp4 |
32.92Мб |
| 7. Monitoring Your Model.srt |
11.99Кб |
| 7. The Learning Algorithm.mp4 |
24.02Мб |
| 7. The Learning Algorithm.srt |
9.18Кб |
| 8. Ensemble Methods (Bagging, Boosting, Stacking).mp4 |
7.50Мб |
| 8. Ensemble Methods (Bagging, Boosting, Stacking).srt |
5.15Кб |
| 8. Quiz #2 When to ML.html |
188б |
| 8. Quiz #3 How to ML.html |
188б |
| 8. Quiz #7 Deploy Your Model.html |
188б |
| 8. Storing Data Warehouses, Lakes & Graphs.mp4 |
25.62Мб |
| 8. Storing Data Warehouses, Lakes & Graphs.srt |
9.90Кб |
| 8. Types of ML.mp4 |
52.29Мб |
| 8. Types of ML.srt |
10.95Кб |
| 9. Congratulations!.mp4 |
19.01Мб |
| 9. Congratulations!.srt |
1.31Кб |
| 9. Exercise #2 What Type of ML is This.mp4 |
30.17Мб |
| 9. Exercise #2 What Type of ML is This.srt |
7.93Кб |
| 9. Quiz #4 Get Your Data.html |
188б |
| 9. Quiz #6 Build Your Model.html |
188б |
| Bonus Resources.txt |
357б |
| Get Bonus Downloads Here.url |
177б |