Guns-229's starred repositories
Diffusion-Models-pytorch
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
pytorch-stable-diffusion
Stable Diffusion implemented from scratch in PyTorch
stablediffusion
High-Resolution Image Synthesis with Latent Diffusion Models
generativemusicaicourse
Resources for the Generative Music AI Course on The Sound of AI YouTube channel.
udacity-natural-language-processing-nanodegree
Exercises, projects and solutions for Udacity Natural Language Processing Nanodegree program
generative-ai
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
Transformers-for-NLP-2nd-Edition
Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more
AdversarialNetsPapers
Awesome paper list with code about generative adversarial nets
awesome-project-ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
Data-Science-Projects
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
500 AI Machine learning Deep learning Computer vision NLP Projects with code
Hands-On-Data-Structures-and-Algorithms-with-Python-Second-Edition
Hands-On Data Structures and Algorithms with Python Second Edition, published by Packt
Data-Structures-and-Algorithms
A repository to help the open-source community with DSA related contributions
Data-Structures-and-Algorithms-Python
All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.
Generative-AI-with-LLMs
Generative AI with Large Language Models (LLMs) - how generative AI works, and how to deploy it in real-world applications. Coursera link -> https://www.coursera.org/learn/generative-ai-with-llms
Generative_AI_LLMs
Generative AI with Large Language Models on Coursera offered by Deeplearning.AI and AWS.
Generative-AI-with-LLMs
In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
diffusion-nbs
Getting started with diffusion
coursera-ai-for-medicine-specialization
Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai
DeepLearning.AI-Deep-Learning-Specialization
This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI
coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Coursera-Applied-Machine-Learning-with-Python-
This repository contains solutions of all assignments of University of Michigan's Applied Machine Learning with python course.
Machine-Learning-WASHINGTON-Course-1
COURSERA - Machine Learning Foundations: A Case Study Approach (by University of Washington)
Machine-Learning-Foundations
Machine Learning Foundations: A Case Study Approach by University of Washington, Coursera
Machine-Learning-University-of-Washington
My machine learning projects about regression, classification and clustering
Machine-Learning-Specialization-University-of-Washington-
Coursera Assignment and Project
Introduction-to-Data-Science-in-Python
Coursera | Introduction to Data Science in Python（University of Michigan）
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media