# 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 | [Introduction](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/README) | Learn the basic concepts behind machine learning | [Lesson](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/1-intro-to-ML/README) | Muhammad | | 02 | The History of machine learning | [Introduction](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/README) | Learn the history underlying this field | [Lesson](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/2-history-of-ML/README) | Jen and Amy | | 03 | Fairness and machine learning | [Introduction](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/README) | What are the important philosophical issues around fairness that students should consider when building and applying ML models? | [Lesson](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/3-fairness/README) | Tomomi | | 04 | Techniques for machine learning | [Introduction](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/README) | What techniques do ML researchers use to build ML models? | [Lesson](https://microsoft.github.io/ML-For-Beginners/#/1-Introduction/4-techniques-of-ML/README) | Chris and Jen | | 05 | Introduction to regression | [Regression](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/README) | Get started with Python and Scikit-learn for regression models | [Python](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/1-Tools/README)[R](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/1-Tools/solution/R/lesson_1-R.ipynb) | JenEric Wanjau | | 06 | North American pumpkin prices 🎃 | [Regression](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/README) | Visualize and clean data in preparation for ML | [Python](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/2-Data/README)[R](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/2-Data/solution/R/lesson_2-R.ipynb) | JenEric Wanjau | | 07 | North American pumpkin prices 🎃 | [Regression](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/README) | Build linear and polynomial regression models | [Python](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/3-Linear/README)[R](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/3-Linear/solution/R/lesson_3-R.ipynb) | Jen and DmitryEric Wanjau | | 08 | North American pumpkin prices 🎃 | [Regression](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/README) | Build a logistic regression model | [Python](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/4-Logistic/README)[R](https://microsoft.github.io/ML-For-Beginners/#/2-Regression/4-Logistic/solution/R/lesson_4-R.ipynb) | JenEric Wanjau | | 09 | A Web App 🔌 | [Web App](https://microsoft.github.io/ML-For-Beginners/#/3-Web-App/README) | Build a web app to use your trained model | [Python](https://microsoft.github.io/ML-For-Beginners/#/3-Web-App/1-Web-App/README) | Jen | | 10 | Introduction to classification | [Classification](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/README) | Clean, prep, and visualize your data; introduction to classification | [Python](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/1-Introduction/README)[R](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb) | Jen and CassieEric Wanjau | | 11 | Delicious Asian and Indian cuisines 🍜 | [Classification](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/README) | Introduction to classifiers | [Python](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/2-Classifiers-1/README)[R](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb) | Jen and CassieEric Wanjau | | 12 | Delicious Asian and Indian cuisines 🍜 | [Classification](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/README) | More classifiers | [Python](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/3-Classifiers-2/README)[R](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/3-Classifiers-2/solution/R/lesson_12-R.ipynb) | Jen and CassieEric Wanjau | | 13 | Delicious Asian and Indian cuisines 🍜 | [Classification](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/README) | Build a recommender web app using your model | [Python](https://microsoft.github.io/ML-For-Beginners/#/4-Classification/4-Applied/README) | Jen | | 14 | Introduction to clustering | [Clustering](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/README) | Clean, prep, and visualize your data; Introduction to clustering | [Python](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/1-Visualize/README)[R](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/1-Visualize/solution/R/lesson_14-R.ipynb) | JenEric Wanjau | | 15 | Exploring Nigerian Musical Tastes 🎧 | [Clustering](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/README) | Explore the K-Means clustering method | [Python](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/2-K-Means/README)[R](https://microsoft.github.io/ML-For-Beginners/#/5-Clustering/2-K-Means/solution/R/lesson_15-R.ipynb) | JenEric Wanjau | | 16 | Introduction to natural language processing ☕️ | [Natural language processing](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/README) | Learn the basics about NLP by building a simple bot | [Python](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/1-Introduction-to-NLP/README) | Stephen | | 17 | Common NLP Tasks ☕️ | [Natural language processing](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/README) | Deepen your NLP knowledge by understanding common tasks required when dealing with language structures | [Python](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/2-Tasks/README) | Stephen | | 18 | Translation and sentiment analysis ♥️ | [Natural language processing](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/README) | Translation and sentiment analysis with Jane Austen | [Python](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/3-Translation-Sentiment/README) | Stephen | | 19 | Romantic hotels of Europe ♥️ | [Natural language processing](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/README) | Sentiment analysis with hotel reviews 1 | [Python](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/4-Hotel-Reviews-1/README) | Stephen | | 20 | Romantic hotels of Europe ♥️ | [Natural language processing](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/README) | Sentiment analysis with hotel reviews 2 | [Python](https://microsoft.github.io/ML-For-Beginners/#/6-NLP/5-Hotel-Reviews-2/README) | Stephen | | 21 | Introduction to time series forecasting | [Time series](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/README) | Introduction to time series forecasting | [Python](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/1-Introduction/README) | Francesca | | 22 | ⚡️ World Power Usage ⚡️ - time series forecasting with ARIMA | [Time series](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/README) | Time series forecasting with ARIMA | [Python](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/2-ARIMA/README) | Francesca | | 23 | ⚡️ World Power Usage ⚡️ - time series forecasting with SVR | [Time series](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/README) | Time series forecasting with Support Vector Regressor | [Python](https://microsoft.github.io/ML-For-Beginners/#/7-TimeSeries/3-SVR/README) | Anirban | | 24 | Introduction to reinforcement learning | [Reinforcement learning](https://microsoft.github.io/ML-For-Beginners/#/8-Reinforcement/README) | Introduction to reinforcement learning with Q-Learning | [Python](https://microsoft.github.io/ML-For-Beginners/#/8-Reinforcement/1-QLearning/README) | Dmitry | | 25 | Help Peter avoid the wolf! 🐺 | [Reinforcement learning](https://microsoft.github.io/ML-For-Beginners/#/8-Reinforcement/README) | Reinforcement learning Gym | [Python](https://microsoft.github.io/ML-For-Beginners/#/8-Reinforcement/2-Gym/README) | Dmitry | | Postscript | Real-World ML scenarios and applications | [ML in the Wild](https://microsoft.github.io/ML-For-Beginners/#/9-Real-World/README) | Interesting and revealing real-world applications of classical ML | [Lesson]( | |