| Topic | Lesson Grouping | Learning Objectives |
|---|---|---|
| Introduction to machine learning | Introduction | Learn the basic concepts behind machine learning |
| The History of machine learning | Introduction | Learn the history underlying this field |
| Fairness and machine learning | Introduction | What are the important philosophical issues around fairness that students should consider when building and applying ML models? |
| Techniques for machine learning | Introduction | What techniques do ML researchers use to build ML models? |
| Introduction to regression | Regression | Get started with Python and Scikit-learn for regression models |
| North American pumpkin prices聽馃巸 | Regression | Visualize and clean data in preparation for ML |
| North American pumpkin prices聽馃巸 | Regression | Build linear and polynomial regression models |
| North American pumpkin prices聽馃巸 | Regression | Build a logistic regression model |
| A Web App聽馃攲 | Web App | Build a web app to use your trained model |
| Introduction to classification | Classification | Clean, prep, and visualize your data; introduction to classification |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | Introduction to classifiers |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | More classifiers |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | Build a recommender web app using your model |
| Introduction to clustering | Clustering | Clean, prep, and visualize your data; Introduction to clustering |
| Exploring Nigerian Musical Tastes聽馃帶 | Clustering | Explore the K-Means clustering method |
| Introduction to natural language processing聽鈽曪笍 | Natural language processing | Learn the basics about NLP by building a simple bot |
| Common NLP Tasks聽鈽曪笍 | Natural language processing | Deepen your NLP knowledge by understanding common tasks required when dealing with language structures |
| Translation and sentiment analysis聽鈾ワ笍 | Natural language processing | Translation and sentiment analysis with Jane Austen |
| Romantic hotels of Europe聽鈾ワ笍 | Natural language processing | Sentiment analysis with hotel reviews, 1 |
| Romantic hotels of Europe聽鈾ワ笍 | Natural language processing | Sentiment analysis with hotel reviews 2 |
| Introduction to time series forecasting | Time series | Introduction to time series forecasting |
| 鈿★笍聽World Power Usage聽鈿★笍聽- time series forecasting with ARIMA | Time series | Time series forecasting with ARIMA |
| Introduction to reinforcement learning | Reinforcement learning | Introduction to reinforcement learning with Q-Learning |
| Help Peter avoid the wolf!聽馃惡 | Reinforcement learning | Reinforcement learning Gym |
| Real-World ML scenarios and applications | ML in the Wild | Interesting and revealing real-world applications of classical ML |
| Topic | Lesson Grouping | Learning Objectives |
|---|---|---|
| Introduction to machine learning | Introduction | Learn the basic concepts behind machine learning |
| The History of machine learning | Introduction | Learn the history underlying this field |
| Fairness and machine learning | Introduction | What are the important philosophical issues around fairness that students should consider when building and applying ML models? |
| Techniques for machine learning | Introduction | What techniques do ML researchers use to build ML models? |
| Introduction to regression | Regression | Get started with Python and Scikit-learn for regression models |
| North American pumpkin prices聽馃巸 | Regression | Visualize and clean data in preparation for ML |
| North American pumpkin prices聽馃巸 | Regression | Build linear and polynomial regression models |
| North American pumpkin prices聽馃巸 | Regression | Build a logistic regression model |
| A Web App聽馃攲 | Web App | Build a web app to use your trained model |
| Introduction to classification | Classification | Clean, prep, and visualize your data; introduction to classification |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | Introduction to classifiers |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | More classifiers |
| Delicious Asian and Indian cuisines聽馃崪 | Classification | Build a recommender web app using your model |
| Introduction to clustering | Clustering | Clean, prep, and visualize your data; Introduction to clustering |
| Exploring Nigerian Musical Tastes聽馃帶 | Clustering | Explore the K-Means clustering method |
| Introduction to natural language processing聽鈽曪笍 | Natural language processing | Learn the basics about NLP by building a simple bot |
| Common NLP Tasks聽鈽曪笍 | Natural language processing | Deepen your NLP knowledge by understanding common tasks required when dealing with language structures |
| Translation and sentiment analysis聽鈾ワ笍 | Natural language processing | Translation and sentiment analysis with Jane Austen |
| Romantic hotels of Europe聽鈾ワ笍 | Natural language processing | Sentiment analysis with hotel reviews, 1 |
| Romantic hotels of Europe聽鈾ワ笍 | Natural language processing | Sentiment analysis with hotel reviews 2 |
| Introduction to time series forecasting | Time series | Introduction to time series forecasting |
| 鈿★笍聽World Power Usage聽鈿★笍聽- time series forecasting with ARIMA | Time series | Time series forecasting with ARIMA |
| Introduction to reinforcement learning | Reinforcement learning | Introduction to reinforcement learning with Q-Learning |
| Help Peter avoid the wolf!聽馃惡 | Reinforcement learning | Reinforcement learning Gym |
| Real-World ML scenarios and applications | ML in the Wild | Interesting and revealing real-world applications of classical ML |
Technology
Machine Learning
computer science
technology
ArtificialIntelligence
Microsoft
Comments
路
0
You need to be Logged in to Comment. Login
