Microsoft
Microsoft#
https://learn.microsoft.com/zh-cn/
https://microsoft.github.io/ai-edu/
https://microsoft.github.io/ML-For-Beginners/#/
https://www.coursera.org/learn/microsoft-azure-machine-learning
Lesson Number |
Topic |
Lesson Grouping |
Learning Objectives |
Linked Lesson |
Author |
---|---|---|---|---|---|
01 |
Introduction to machine learning |
Learn the basic concepts behind machine learning |
Muhammad |
||
02 |
The History of machine learning |
Learn the history underlying this field |
Jen and Amy |
||
03 |
Fairness and machine learning |
What are the important philosophical issues around fairness that students should consider when building and applying ML models? |
Tomomi |
||
04 |
Techniques for machine learning |
What techniques do ML researchers use to build ML models? |
Chris and Jen |
||
05 |
Introduction to regression |
Get started with Python and Scikit-learn for regression models |
JenEric Wanjau |
||
06 |
North American pumpkin prices 🎃 |
Visualize and clean data in preparation for ML |
JenEric Wanjau |
||
07 |
North American pumpkin prices 🎃 |
Build linear and polynomial regression models |
Jen and DmitryEric Wanjau |
||
08 |
North American pumpkin prices 🎃 |
Build a logistic regression model |
JenEric Wanjau |
||
09 |
A Web App 🔌 |
Build a web app to use your trained model |
Jen |
||
10 |
Introduction to classification |
Clean, prep, and visualize your data; introduction to classification |
Jen and CassieEric Wanjau |
||
11 |
Delicious Asian and Indian cuisines 🍜 |
Introduction to classifiers |
Jen and CassieEric Wanjau |
||
12 |
Delicious Asian and Indian cuisines 🍜 |
More classifiers |
Jen and CassieEric Wanjau |
||
13 |
Delicious Asian and Indian cuisines 🍜 |
Build a recommender web app using your model |
Jen |
||
14 |
Introduction to clustering |
Clean, prep, and visualize your data; Introduction to clustering |
JenEric Wanjau |
||
15 |
Exploring Nigerian Musical Tastes 🎧 |
Explore the K-Means clustering method |
JenEric Wanjau |
||
16 |
Introduction to natural language processing ☕️ |
Learn the basics about NLP by building a simple bot |
Stephen |
||
17 |
Common NLP Tasks ☕️ |
Deepen your NLP knowledge by understanding common tasks required when dealing with language structures |
Stephen |
||
18 |
Translation and sentiment analysis ♥️ |
Translation and sentiment analysis with Jane Austen |
Stephen |
||
19 |
Romantic hotels of Europe ♥️ |
Sentiment analysis with hotel reviews 1 |
Stephen |
||
20 |
Romantic hotels of Europe ♥️ |
Sentiment analysis with hotel reviews 2 |
Stephen |
||
21 |
Introduction to time series forecasting |
Introduction to time series forecasting |
Francesca |
||
22 |
⚡️ World Power Usage ⚡️ - time series forecasting with ARIMA |
Time series forecasting with ARIMA |
Francesca |
||
23 |
⚡️ World Power Usage ⚡️ - time series forecasting with SVR |
Time series forecasting with Support Vector Regressor |
Anirban |
||
24 |
Introduction to reinforcement learning |
Introduction to reinforcement learning with Q-Learning |
Dmitry |
||
25 |
Help Peter avoid the wolf! 🐺 |
Reinforcement learning Gym |
Dmitry |
||
Postscript |
Real-World ML scenarios and applications |
Interesting and revealing real-world applications of classical ML |
[Lesson]( |