딥러닝 기본과 NLP를 익히는데 도움이 될 만한 최신 (2020년 2021년) 동영상 강좌 13종입니다. 하나 하나 직접 들어본 분의 추천이니

딥러닝 기본과 NLP를 익히는데 도움이 될 만한 최신 (2020년 2021년) 동영상 강좌 13종입니다.

하나 하나 직접 들어본 분의 추천이니 관심 있으신 분들은 보시면 좋을 듯 합니다.

1. Deep Learning: CS 182 Spring 2021
Includes a great introduction to deep learning starting with the machine learning basics moving into more core topics like optimization. (by Sergey Levine)

2. Deep Learning (with PyTorch)

This is one of the most recent deep learning courses focusing on hot topics like self-supervised learning, transformers, and energy based models. (by Alfredo Canziani)

3. Deep Learning Crash Course 2021
This course is focused on the popular free book available on the d2l.ai website. If you have been studying the book, this set of lectures will come in handy. (by Alex Smola)

4. Natural Language Processing
If you are not too familiar with natural language processing (NLP) concepts, this is a great place to start. It provides short and accessible summaries of some of the most important techniques used to solve NLP problems. (by Machine Learning University)

5. CMU Neural Nets for NLP 2021
This course covers topics related to how neural networks are used in natural language processing (NLP). (by Graham Neubig)

6. CS224N: Natural Language Processing with Deep Learning
This has been one of the most popular NLP courses for some time now. It focuses on the use of the latest deep learning techniques applied to NLP problems. (by Chris Manning)

7. fast.ai Code-First Intro to Natural Language Processing
The NLP courses above focus heavily on the theory. To get the practical side of NLP, this fast.ai course will be a great place to start. (by Rachel Thomas)

8. CMU Multilingual NLP 2020
Graham Neubig also provides another great course that focuses on multilingual NLP. Topics range from data annotation to code switching to low resource automatic speech recognition. (by Graham Neubig)

9. Deep Learning for Computer Vision 2020
This course focuses heavily on the latest techniques in deep learning for computer vision tasks. From attention mechanism to generative models. (by Justin Johnson)

10. Deep Reinforcement Learning: CS 285 Fall 2020
Focuses on the use of deep learning-based architectures for reinforcement learning problems. (by Sergey Levine)

11. Full Stack Deep Learning 2021
While most of the courses above focus heavily on theory, this course specifically focuses on the ecosystem of tools used to develop and deploy deep learning models. (by Josh Tobin, Pieter Abbeel, Sergey Karayev)

12. Practical Deep Learning for Coders
This is another course by fast.ai focusing on a coder-first approach to deep learning. (by Jeremy Howard)

13. Applied ML
This is an ongoing course teaching how to build a product grade product through ML techniques and tools. (by Made with ML)