Courses
- Scikit-learn course
(link)
- Introduction to Machine Learning - Raschka
(link)
- Introduction to Deep Learning - Raschka
(link)
- Hugging Face Course
(link)
- Functions, Tools and Agents with LangChain
(link)
- Building Your Own Database Agent
(link)
- Time Series - Kaggle
(link)
- Dive into Deep Learning
(link)
- CS231n: Convolutional Neural Networks for Visual Recognition
(link)
- DEEP LEARNING - LeCun, Canziani
(link)
- NLP Zero to One: Full Course
(link)
- Mathematical Tools for Data Science
(link)
- UMass CS685 (Advanced NLP)
(link)
- DeepMind x UCL | Deep Learning Lecture Series 2020
(link)
- Linear Algebra - Strang Videos
(link)
- Natural Language Processing
(link)
- Spring 2019 Full Stack Deep Learning Bootcamp
(link)
- CMU Neural Nets for NLP 2019
(link)
- Stanford CS224N: NLP with Deep Learning | Winter 2021
(link)
- opensap
(link)
- openhpi
(link)
- In-Memory Data Management
(link)
- CS224n: Natural Language Processing with Deep Learning - Manning
(link)
- CMU: Neural Networks for NLP - Neubig
(link)
- Deep Learning for Text and Sequences Goldberg
(link)
- Intro to Deep Learning with PyTorch - Udacity
(link)
- Course - EE-559 – Deep Learning (Spring 2019)
(link)
- Time Series video course
(link)
Books
- 14 Awesome Free Books for Machine Learning, Deep Learning & Reinforcement Learning
(link)
- An Introduction to Statistical Learning
(link)
- Data Analytics - A Small Data Approach
(link)
- Elements of Data Science
(link)
- Interpretable Machine Learning
(link)
- Mathematics for Machine Learning
(link)
- Patterns, Predictions, and Actions
(link)
- Pattern Recognition and Machine Learning
(link)
- Probabilistic Machine Learning: An Introduction
(link)
- Principles of Distributed Database Systems
(link)
- Speech and Language Processing
(link)
- The fastai book
(link)
- The Mechanics of Machine Learning
(link)
- Think Bayes 2
(link)