deep-learning
# Courses
I.
fastai
II.
Deep Learning Specialization\
# Textbooks
I.
Deep Learning
II.
Neural networks and deep learning
III.
Deep Learning with Python, Second Edition
# Playlists
I. Neural Networks: Zero to Hero - YouTube II. Practical Deep Learning for Coders 2022 - YouTube III. Neural Networks - 3blue1brown IV. Deep Learning for Computer Vision - YouTube V. DeepMind x UCL | Deep Learning Lecture Series 2021 - YouTube VI. Stanford CS234: Reinforcement Learning | Winter 2019 - YouTube VII. Deep Reinforcement Learning: CS 285 Fall 2021 (UC Berkeley) - YouTube VIII. CS839 Special Topics in Deep Learning: Course Overview (Lecture 1) - YouTube IX. AMMI Geometric Deep Learning Course - Second Edition (2022) - YouTube X. Princeton ORFE Deep Learning Theory Summer School 2021 - YouTube XI. Deep Learning in Life Sciences - Lecture 01 - Course Intro, AI, ML (Spring 2021) - YouTube
# Podcasts
# Deep Learning State of the Art (2020) - Lex Fridman (YT) 24:24
- Jurgen Schmidhuber - Deep Learning in Neural Networks: An Overview
- Rebooting AI - Gary Marcus
- AI - A guide for thinking humans - Melanie Mitchell
- Research Topics
- Reasoning
- Active learning and life-long learning
- Multi-modal and multitask learning
- Open-domain conversation
- Applications: medical, autonomous vehicles
- Algorithmic Ethics
- Computer Robotics
- Frameworks
- TensorFlow 2.0
- PyTorch 1.3
- Reinforcement Learning Frameworks
- “Stable Baselines” (OpenAI Baselines Fork) * Natural Language Processing
- sebastianruder/NLP-progress
- Transformer
- BERT (Google)
- XLNet (Google/CMU)
- GPT-2 (OpenAI)
- ALBERT (Google/Toyota)
- Megatron (NVIDIA)
- BERT Applications
- Create contextualized word embeddings (like ELMo)
- Sentence classification
- Sentence pair classification
- Sentence pair similarity
- Multiple Choice
- Sentence Tagging
- Question Answering