InfoCoBuild

6.S191 Introduction to Deep Learning

6.S191 Introduction to Deep Learning (January IAP 2020, MIT OCW). Instructors: Alexander Amini and Ava Soleimany. This is MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), and we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. (from ocw.mit.edu)

Lecture 10 - Machine Learning for Scent


Go to the Course Home or watch other lectures:

2022 Lectures
Lecture 01 - Introduction
Lecture 02 - Recurrent Neural Networks and Transformers
Lecture 03 - Convolutional Neural Networks
Lecture 04 - Deep Generative Modeling
Lecture 05 - Reinforcement Learning
Lecture 06 - Deep Learning New Frontiers
Lecture 07 - LiDAR for Autonomous Driving
2021 Lectures
Lecture 01 - Introduction
Lecture 02 - Recurrent Neural Networks
Lecture 03 - Convolutional Neural Networks
Lecture 04 - Deep Generative Modeling
Lecture 05 - Reinforcement Learning
Lecture 06 - Deep Learning New Frontiers
Lecture 07 - Evidential Deep Learning and Uncertainty
Lecture 08 - AI Bias and Fairness
Lecture 09 - Deep CPCFG for Information Extraction
Lecture 10 - Taming Dataset Bias via Domain Adaptation
Lecture 11 - Towards AI for 3D Content Creation
Lecture 12 - AI in Healthcare
2020 Lectures
Lecture 01 - Introduction
Lecture 02 - Recurrent Neural Networks
Lecture 03 - Convolutional Neural Networks
Lecture 04 - Deep Generative Modeling
Lecture 05 - Reinforcement Learning
Lecture 06 - Deep Learning New Frontiers
Lecture 07 - Neurosymbolic AI
Lecture 08 - Generalizable Autonomy for Robot Manipulation
Lecture 09 - Neural Rendering
Lecture 10 - Machine Learning for Scent