Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
- gpt
- large-language-models
- llm
- python
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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Learn how to develop, deploy and iterate on production-grade ML applications.
Translated✅ (Completed) Super comprehensive deep learning notes [Tudui PyTorch] [Li Mu Dive into Deep Learning] [Andrew Ng Deep Learning] [Dafei LLM Agent]
TranslatedThis project changes the MXNet implementations in the original book 《动手学深度学习》 (Dive into Deep Learning) into PyTorch implementations.
Natural Language Processing Tutorial for Deep Learning Researchers
YSDA course in Natural Language Processing
Collection of notebooks about quantitative finance, with interactive python code.
Jupyter notebooks for the Natural Language Processing with Transformers book
Think DSP: Digital Signal Processing in Python, by Allen B. Downey.
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Build a modern LLM from scratch. Every line commented. Explained like we are five.
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
Open Machine Learning course
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)
NMA Computational Neuroscience course
The Python Code Tutorials
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
Machine Learning University: Accelerated Natural Language Processing Class
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Materials for GWU DNSC 6279 and DNSC 6290.
Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
Exercises for the lecture "Selected Topics in Audio Signal Processing"