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S# Lecture Course Institute Instructor Discipline
1776
Deep Learning Limitations and New Frontiers (M-I-T)
Deep Learning (2020) (M-I-T) MIT Ava Soleimany Applied Sciences
1777
Two-dimensional linear regression – demo (M-I-T)
Introduction to Machine Learning (Fall 2020) (M-I-T) MIT Prof. Leslie Kaelbling Applied Sciences
1778
Deep Learning New Frontiers (M-I-T)
Deep Learning (2020) (M-I-T) MIT Ava Soleimany Applied Sciences
1779
 Bagging – bootstrap aggregation of models (M-I-T)
Introduction to Machine Learning (Fall 2020) (M-I-T) MIT Prof. Leslie Kaelbling Applied Sciences
1780
Faster ML Development with TensorFlow (M-I-T)
Deep Learning (2020) (M-I-T) MIT Shanqing Cai Applied Sciences
1781
 Decision trees – the good and the bad (M-I-T)
Introduction to Machine Learning (Fall 2020) (M-I-T) MIT Prof. Leslie Kaelbling Applied Sciences
1782
Generalizable Autonomy for Robot Manipulation (M-I-T)
Deep Learning (2020) (M-I-T) MIT Chuan Li Applied Sciences
1783
 Neural networks – backprop with the chain rule (M-I-T)
Introduction to Machine Learning (Fall 2020) (M-I-T) MIT Prof. Leslie Kaelbling Applied Sciences
1784
Image Domain Transfer (NVIDIA) (M-I-T)
Deep Learning (2020) (M-I-T) MIT Jan Kautz Applied Sciences
1785
Introduction to Deep Learning (M-I-T)
Deep Learning (2020) (M-I-T) MIT David Cox Applied Sciences
1786
Machine Learning for Scent (M-I-T)
Deep Learning (2020) (M-I-T) MIT Barack Obama Applied Sciences
1787
Neural Rendering (M-I-T)
Deep Learning (2020) (M-I-T) MIT Alex Wiltschko Applied Sciences
1788
Neurosymbolic AI (M-I-T)
Deep Learning (2020) (M-I-T) MIT Animesh Garg Applied Sciences
1789
Recurrent Neural Networks (M-I-T)
Deep Learning (2020) (M-I-T) MIT Ava Soleimany Applied Sciences
1790
Reinforcement Learning (M-I-T)
Deep Learning (2020) (M-I-T) MIT Alexander Amini Applied Sciences
1791
Sequence Modeling with Neural Networks (M-I-T)
Deep Learning (2020) (M-I-T) MIT Harini Suresh Applied Sciences
1792
Visualization for Machine Learning (Google Brain) (M-I-T)
Deep Learning (2020) (M-I-T) MIT Fernanda Viegas Applied Sciences
1793
 Evidential Deep Learning and Uncertainty (M-I-T)
Deep Learning (2020) (M-I-T) MIT Alexander Amini Applied Sciences
1794
 Introduction to Deep Learning (M-I-T)
Deep Learning (2020) (M-I-T) MIT Alexander Amini Applied Sciences
1795
 Issues in Image Classification (M-I-T)
Deep Learning (2020) (M-I-T) MIT D. Sculley Applied Sciences
1796
Lecture 10: Application of Machine Learning to Cardiac Imaging (M-I-T)
Machine Learning for Healthcare (Spring 2019) (M-I-T) MIT Prof. Dr. Peter Szolovits, Prof. Dr. David Sontag Applied Sciences
1797
Lecture 11: Differential Diagnosis (M-I-T)
Machine Learning for Healthcare (Spring 2019) (M-I-T) MIT Prof. Dr. Peter Szolovits, Prof. Dr. David Sontag Applied Sciences
1798
Lecture 12: Machine Learning for Pathology (M-I-T)
Machine Learning for Healthcare (Spring 2019) (M-I-T) MIT Prof. Dr. Peter Szolovits, Prof. Dr. David Sontag Applied Sciences
1799
Lecture 13: Machine Learning for Mammography (M-I-T)
Machine Learning for Healthcare (Spring 2019) (M-I-T) MIT Prof. Dr. Peter Szolovits, Prof. Dr. David Sontag Applied Sciences
1800
Lecture 14: Causal Inference, Part 1 (M-I-T)
Machine Learning for Healthcare (Spring 2019) (M-I-T) MIT Prof. Dr. Peter Szolovits, Prof. Dr. David Sontag Applied Sciences