Open this github Repo to follow along You can't learn EVERYTHING in ~2 hours, especially when it comes to Machine Learning! But you can learn enough to get excited and comfortable to keep working and ...

Breakout rooms and Office hours will NOT be recorded. Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that learn to ...

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

This week, we will build our supervised machine learning foundation. Data cleaning and Exploratory Data Analysis (EDA) might not seem glamorous, but the process is vital for guiding your real-world ...

This course gives a basic introduction to machine learning (ML) and artificial intelligence (AI). Through an algorithmic approach, the students are given a practical understanding of the methods being ...

Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that learn to recognize human faces, recommend music and movies, ...

Note that it isn’t exactly trivial for us to work out the weights just by inspection alone. Many machine learning models allow some randomness in model training. Specifying a number for random_state ...

This course covers modern machine learning theory and techniques that can be applied to make informed data-driven decisions. Instead of manually analyzing data, machine learning offers a more ...

Summer School Teacher Interview: ‘The future will be shaped by AI and ML in ways we can only begin to imagine’ Dariush Salami is teaching the brand new summer course Intro to AI and Machine Learning ...