| 1. Congratulations! You Are Now An ML Product Manager.mp4 | 5.5 MB | ||
| 1. Congratulations! You Are Now An ML Product Manager.srt | 3.1 KB | ||
| 1. Data Acquisition Strategies.mp4 | 42.7 MB | ||
| 1. Data Acquisition Strategies.srt | 14.2 KB | ||
| 1. Data Scrubbing.mp4 | 15.3 MB | ||
| 1. Data Scrubbing.srt | 9.6 KB | ||
| 1. How the ML PM's Role Differs.mp4 | 8.6 MB | ||
| 1. How the ML PM's Role Differs.srt | 4.1 KB | ||
| 1. The AI Flywheel.mp4 | 26.2 MB | ||
| 1. The AI Flywheel.srt | 5.9 KB | ||
| 1. The Confusion Matrix.mp4 | 32.3 MB | ||
| 1. The Confusion Matrix.srt | 6 KB | ||
| 1. Which ML algorithm should I use.mp4 | 6.2 MB | ||
| 1. Which ML algorithm should I use.srt | 3.3 KB | ||
| 10. Deep Learning.mp4 | 34.7 MB | ||
| 10. Deep Learning.srt | 9.7 KB | ||
| 11. ML Real World Examples.mp4 | 34.5 MB | ||
| 11. ML Real World Examples.srt | 6.2 KB | ||
| 12. ML Terminology.mp4 | 12.1 MB | ||
| 12. ML Terminology.srt | 4.5 KB | ||
| 13. Exercise #3 Apply your ML Lingo.mp4 | 40.4 MB | ||
| 13. Exercise #3 Apply your ML Lingo.srt | 9.1 KB | ||
| 14. Quiz #1 ML Introduction.html | 204.8 B | ||
| 2. Build, Outsource or Buy Your ML Solution.mp4 | 13 MB | ||
| 2. Build, Outsource or Buy Your ML Solution.srt | 6.3 KB | ||
| 2. Evaluation Metrics (Precision, Recall & F1 Score).mp4 | 51.8 MB | ||
| 2. Evaluation Metrics (Precision, Recall & F1 Score).srt | 9.8 KB | ||
| 2. Google reCAPTCHA.mp4 | 50.5 MB | ||
| 2. Google reCAPTCHA.srt | 6 KB | ||
| 2. ML Product Horror Stories.mp4 | 65.5 MB | ||
| 2. ML Product Horror Stories.srt | 8 KB | ||
| 2. Organizing ML Teams.mp4 | 27.3 MB | ||
| 2. Organizing ML Teams.srt | 7.3 KB | ||
| 2. Sampling and Splitting Data.mp4 | 16.6 MB | ||
| 2. Sampling and Splitting Data.srt | 6.6 KB | ||
| 2. What is Machine Learning (ML).mp4 | 18.2 MB | ||
| 2. What is Machine Learning (ML).srt | 6 KB | ||
| 2.1 IBM Watson Failure.html | 102.4 B | ||
| 2.2 Racial Bias In Facial Recognition Tools.html | 204.8 B | ||
| 3. Adjusting Course Speed.html | 614.4 B | ||
| 3. Exercise #12 Lets Calculate Evaluation Metrics.mp4 | 18.5 MB | ||
| 3. Exercise #12 Lets Calculate Evaluation Metrics.srt | 9.2 KB | ||
| 3. Exercise #9 Find Examples of User-Generated Data Labelling.mp4 | 23.8 MB | ||
| 3. Exercise #9 Find Examples of User-Generated Data Labelling.srt | 4.6 KB | ||
| 3. Key Roles in An ML Team.mp4 | 24.4 MB | ||
| 3. Key Roles in An ML Team.srt | 10 KB | ||
| 3. Machine Learning as a Service (MLaaS).mp4 | 76.8 MB | ||
| 3. Machine Learning as a Service (MLaaS).srt | 10.3 KB | ||
| 3. Transforming Data.mp4 | 13.3 MB | ||
| 3. Transforming Data.srt | 7.9 KB | ||
| 3. When to ML.mp4 | 13.8 MB | ||
| 3. When to ML.srt | 5.4 KB | ||
| 4. Feature Engineering.mp4 | 6.2 MB | ||
| 4. Feature Engineering.srt | 3.6 KB | ||
| 4. ML is Going Mainstream.mp4 | 50.7 MB | ||
| 4. ML is Going Mainstream.srt | 10.9 KB | ||
| 4. Regression (Linear, Polynomial, Logistic).mp4 | 10.7 MB | ||
| 4. Regression (Linear, Polynomial, Logistic).srt | 7.4 KB | ||
| 4. Start with a Simplified Problem.mp4 | 7.8 MB | ||
| 4. Start with a Simplified Problem.srt | 3.3 KB | ||
| 4. The ML Life Cycle.mp4 | 51.6 MB | ||
| 4. The ML Life Cycle.srt | 21.2 KB | ||
| 4. User Experience Optimization.mp4 | 20.3 MB | ||
| 4. User Experience Optimization.srt | 8.6 KB | ||
| 4. When not to ML.mp4 | 9 MB | ||
| 4. When not to ML.srt | 4.8 KB | ||
| 5. Classification (SVM, K-NN, Decision Trees).mp4 | 27.7 MB | ||
| 5. Classification (SVM, K-NN, Decision Trees).srt | 14 KB | ||
| 5. Exercise #10 Design Your Data for The Model.mp4 | 14.5 MB | ||
| 5. Exercise #10 Design Your Data for The Model.srt | 4.4 KB | ||
| 5. Exercise #11 Brainstorm a new feature.mp4 | 16.8 MB | ||
| 5. Exercise #11 Brainstorm a new feature.srt | 5.3 KB | ||
| 5. Exercise #13 Precision, Recall or F1 score.mp4 | 25 MB | ||
| 5. Exercise #13 Precision, Recall or F1 score.srt | 8.4 KB | ||
| 5. Exercise #4 Need interpretability.mp4 | 36.7 MB | ||
| 5. Exercise #4 Need interpretability.srt | 9.4 KB | ||
| 5. Exercise#6 Create & Test Your Hypothesis.mp4 | 48.2 MB | ||
| 5. Exercise#6 Create & Test Your Hypothesis.srt | 12.2 KB | ||
| 5. Get Your Course Workbook.html | 614.4 B | ||
| 5.1 Right to Explanation.html | 102.4 B | ||
| 6. Clustering (K-Means, Means Shift).mp4 | 17 MB | ||
| 6. Clustering (K-Means, Means Shift).srt | 8.4 KB | ||
| 6. Deployment Methods.mp4 | 18.4 MB | ||
| 6. Deployment Methods.srt | 8.4 KB | ||
| 6. Exercise #1 Pick Your Product.mp4 | 25.1 MB | ||
| 6. Exercise #1 Pick Your Product.srt | 6.5 KB | ||
| 6. Exercise #7 Frame Your ML Problem.mp4 | 16.5 MB | ||
| 6. Exercise #7 Frame Your ML Problem.srt | 5.2 KB | ||
| 6. ML Data Considerations.mp4 | 8.3 MB | ||
| 6. ML Data Considerations.srt | 3.9 KB | ||
| 6. Quiz #5 Prepare Your Data.html | 204.8 B | ||
| 6. Top Open Data Sources.mp4 | 68.2 MB | ||
| 6. Top Open Data Sources.srt | 7.2 KB | ||
| 7. Anomaly Detection (Local Outlier Factor, DBSCAN).mp4 | 14.2 MB | ||
| 7. Anomaly Detection (Local Outlier Factor, DBSCAN).srt | 7.1 KB | ||
| 7. Exercise #5 To ML or Not to ML.mp4 | 75.1 MB | ||
| 7. Exercise #5 To ML or Not to ML.srt | 17.4 KB | ||
| 7. Exercise #8 Formulate Your ML Problem.mp4 | 26.4 MB | ||
| 7. Exercise #8 Formulate Your ML Problem.srt | 6.3 KB | ||
| 7. How Much Data Do I Need.mp4 | 10.6 MB | ||
| 7. How Much Data Do I Need.srt | 6.5 KB | ||
| 7. Monitoring Your Model.mp4 | 32.9 MB | ||
| 7. Monitoring Your Model.srt | 12 KB | ||
| 7. The Learning Algorithm.mp4 | 24 MB | ||
| 7. The Learning Algorithm.srt | 9.2 KB | ||
| 8. Ensemble Methods (Bagging, Boosting, Stacking).mp4 | 7.5 MB | ||
| 8. Ensemble Methods (Bagging, Boosting, Stacking).srt | 5.1 KB | ||
| 8. Quiz #2 When to ML.html | 204.8 B | ||
| 8. Quiz #3 How to ML.html | 204.8 B | ||
| 8. Quiz #7 Deploy Your Model.html | 204.8 B | ||
| 8. Storing Data Warehouses, Lakes & Graphs.mp4 | 25.6 MB | ||
| 8. Storing Data Warehouses, Lakes & Graphs.srt | 9.9 KB | ||
| 8. Types of ML.mp4 | 52.3 MB | ||
| 8. Types of ML.srt | 11 KB | ||
| 9. Congratulations!.mp4 | 19 MB | ||
| 9. Congratulations!.srt | 1.3 KB | ||
| 9. Exercise #2 What Type of ML is This.mp4 | 30.2 MB | ||
| 9. Exercise #2 What Type of ML is This.srt | 7.9 KB | ||
| 9. Quiz #4 Get Your Data.html | 204.8 B | ||
| 9. Quiz #6 Build Your Model.html | 204.8 B | ||
| Bonus Resources.txt | 307.2 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 122 total files | |||
Machine Learning for Product Managers - A Practical Guide
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.43 GB | Duration: 4h 40m
Kick start your career as a Machine Learning Product Manager with just one course.
What you'll learn
When and how machine learning can be applied to solve problems
How to organize machine learning teams
Key roles in a machine learning team
How to build and test a hypothesis
Popular machine learning algorithms & how they work
Data acquisition strategies
Data scrubbing & transformation
Model evaluation approaches
Model deployment options
Model monitoring
Description
Welcome to Machine Learning for Product Managers, the course designed to help you unlock a career in the lucrative and rapidly growing field of artificial intelligence.
Most machine learning courses focus on the technical work, and throw you into the deep end, asking you to start programming classifiers. This course covers machine learning, from a non-technical, product-centric perspective.
We'll look beyond the technicalities, at all the things a Machine Learning Product Manager has to keep in mind, to create a successful product.
https://TutSala.com
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 779 MB | freecoursewb | 1 week | 1 | 25 | |
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Udemy - Spark Machine Learning Project (House Sale Price Prediction) Posted by
freecoursewb in Other
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1.7 GB | freecoursewb | 1 month | 9 | 4 |
| 3.4 GB | freecoursewb | 1 month | 19 | 5 | |
| 1.2 GB | freecoursewb | 1 month | 12 | 3 | |
| 1.9 GB | freecoursewb | 2 months | 9 | 1 |
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