Course: MIT 6.S191: Introduction to Deep Learning

Lecture video: https://youtu.be/uapdILWYTzE

Course website: IntroToDeepLearning.com

Lecturers: Alexander Amini and Ava Soleimany

Find all notes for this course in the ML Course Notes repo.

Please note that this is a rough draft of the notes, so you might find mistakes. The visuals and equations are directly obtained from the original slides which you can find on the course website. All of the credit goes to the lecturers. I simply hope that the notes serve as accompanying study material. The lecturers use TensorFlow but I am converting all codes to PyTorch.

Computer vision is already making a tremendous impact in various fields and applications.

Deep learning has taken computer vision by storm because of the ability to learn directly from raw pixels and directly from data. Deep learning systems possess the ability to extract meaningful features by observing large corpus of datasets. An example is facial detection and recognition.

Another example is self-driving cars: