📚 Excellent Learning Resources

🌱 Fundamental Deep Learning

Resource NameDescriptionGitHubNotes
Physics Informed Machine LearningApplication of ML methods to physics problems with physical constraints-YouTube Playlist
NUS CS5242 Neural Networks and Deep Learning (2025)Lecture notes and implementations on neural networks and TransformersGitHub LinkTransformer Notes
All about Deep LearningComprehensive repo covering NLP, Tensorflow, Pytorch, and recommendation systemsGitHub Link 
A collection of various DL models (Sebastian Raschka)Collection of DL architectures, implementations, and practical tipsGitHub Link 
Deep Learning from ScratchImplementation of deep learning algorithms from first principlesGitHub LinkBook

👁️ Computer Vision

Resource NameDescriptionGitHubNotes
Vision Transformers from ScratchImplementation of Vision Transformers (ViT) with detailed explanationsGitHub LinkYouTube Tutorial
PyTorch Image Models (timm)Collection of SOTA computer vision models and training scriptsGitHub Link 
Computer Vision Engineer ChannelComprehensive tutorials from basics (YOLO, tracking, pose estimation) to advanced SAAS web apps-YouTube Channel
Object Detection SeriesIn-depth implementation of various object detection algorithmsGitHub LinkYouTube Playlist
Generative Adversarial Networks (GANs)Implementation of various GAN architecturesGitHub LinkYouTube Playlist
Variational Autoencoder from scratchPyTorch implementation of VAE with detailed explanationGitHub LinkYouTube Tutorial
Variational Autoencoders (VAE) in PyTorchExtensive collection of VAE models implemented in PyTorchGitHub Link 
VAE From Scratch ExplainedComplete walkthrough of VAE theory and implementationGitHub LinkYouTube Tutorial
simpleVAE for MNISTTrain VAE on CPU with latent space visualization and number interpolationGitHub LinkYouTube Tutorial
Denoising Diffusion ModelsImplementation of DDPM with training and sampling, mimicking Stable Diffusion architectureGitHub LinkYouTube Tutorial
Stable Diffusion in PyTorchPyTorch implementation of Stable DiffusionGitHub LinkYouTube Tutorial

🗣️ Natural Language Processing (NLP) & 🤖 Large Language Models (LLMs)

Resource NameDescriptionGitHubNotes
BERT from ScratchImplementation of BERT in PyTorch and TensorFlowGitHub Link 
DeepSeek-R1 from ScratchImplementing a smaller model inspired by DeepSeek-R1GitHub LinkBlog (Zhihu)
NLP from Scratch with PyTorchComprehensive guide to building NLP models with PyTorchGitHub Link 
Build LLM Applications from Scratch (Stanford)Course and companion book for LLM application buildingGitHub LinkCompanion book in repo
Build an LLM from Scratch (Sebastian Raschka)Step-by-step LLM building, fine-tuning, and practical examplesGitHub LinkBook, Video Playlist
4-hour LLM Coding WorkshopComprehensive LLM coding workshop by Sebastian RaschkaGitHub LinkYouTube
LLM Lectures by Sebastian RaschkaComprehensive lectures covering multiple LLM topicsGitHub LinkYouTube Playlist
The Illustrated TransformerVisual guide to understanding transformer architecture Blog

🔍 LLM Applications

Resource NameDescriptionGitHubNotes
Neo4j-Labs Text2CypherCollection of datasets, evaluation scripts, and fine-tuning instructions for Text2Cypher modelsGitHub LinkIncludes notebooks for evaluating LLMs on the provided datasets
Neo4j Text2Cypher (2024) DatasetComprehensive dataset for training and evaluating text-to-Cypher conversion modelsGitHub LinkBlog Post
Fine-tuning LLM for Cypher Generation with H2OGuide to fine-tuning an LLM model with H2O LLM Studio to generate Cypher statementsGitHub LinkBlog Post
Cypher Generation - The Good, The Bad, and The MessyMethods for creating fine-tuning datasets for text-to-Cypher generationGitHub LinkBlog Post
Neo4j Text2Cypher - Natural Language QueriesGuide to implementing natural language queries with Neo4j Text2Cypher-Neo4j Labs Guide
Neo4j GraphRAG Text2Cypher Source CodeSource code for the text2cypher retriever in Neo4j’s GraphRAG module-Neo4j Documentation
RetailBanking-ConversationsDataset with 320 realistic banking dialogues for LLM training in financial domainHuggingFace DatasetCreated with WizardSData tool for synthetic datasets
Knowledge Graph-based LLM Dialogue SystemComplete system with data preprocessing, graph construction, graph completion, dialogue model, and web interfaceGitHub Link 
WizardSDataPython library for generating synthetic conversation datasets for fine-tuning models, especially for regulated sectorsGitHub LinkConfigurable roles, conversation length, temperature settings; created by Pere Martra

📈 MLOps & Explainable ML

Resource NameDescriptionGitHubNotes
MLOps BasicsFundamental concepts, implementation of MLOps pipelinesGitHub Link 
Explainable MLTechniques and implementation for explainable machine learning-YouTube Playlist
MLOps ZoomcampComprehensive course on MLOps practices and implementationGitHub LinkYouTube Course

🎵 Audio Processing & Music Generation

Resource NameDescriptionGitHubNotes
Audio Signal Processing for MLAudio processing techniques tailored for machine learning tasksGitHub LinkYouTube Playlist
Audio Data AugmentationComprehensive tutorial on audio data augmentation methodsGitHub LinkYouTube
Generating Sound with Neural NetworksNeural methods for audio synthesisGitHub LinkYouTube Playlist
Melody Generation with RNN-LSTMMusic generation using RNN and LSTM modelsGitHub LinkYouTube Playlist
AudioCraft by MetaFramework for audio generation including MusicGen, AudioGen, and EnCodecGitHub LinkMeta AI Blog

📊 Graph Data Science & Visualization

Resource NameDescriptionGitHubNotes
Stanford CS224W: ML with GraphsStanford’s comprehensive course on graph machine learningGitHub 1, GitHub 2, GitHub 3YouTube Playlist
Graph Convolutional Network (GCN) ExplainedClear explanation and implementation of GCNGitHub LinkYouTube Tutorial
15 Best Graph Visualization ToolsTools for Neo4j graph visualization-Blog Post
PyG (PyTorch Geometric)Library for deep learning on irregular structures like graphsGitHub LinkDocumentation
Awesome Explainable Graph ReasoningCollection of research papers and software for explainability in graph MLGitHub Link 

💰 AI & Quantitative Finance

Resource NameDescriptionGitHubNotes
AI Quant LearningComprehensive systematic learning on quantitative trading strategiesGitHub LinkYouTube Playlist
LLMs in Finance by Hanane DupouyPractical generative AI and AI agents in financeGitHub Link 
Financial Fraud Detection Using LLMsComparing FinBERT and GPT-2 against traditional ML for fraud detectionGitHub LinkBlog
Financial Analysis with LLMNLP application for financial document analysis, detecting suspicious patterns and ML/TF activitiesGitHub Link 
FinRLDeep reinforcement learning framework for financial applicationsGitHub LinkDocumentation
FinLLMOptOptimized LLMs for financial applications including Llama-FinSent-S (pruned LLaMA-3.2-1B) for financial sentiment analysisGitHub Link26% smaller, 50% better instruction-following, 400% better multi-step reasoning
Awesome Fraud Detection PapersCurated list of data mining papers for fraud detectionGitHub Link 

🎯 Machine Learning Interview Preparation

Resource NameDescriptionGitHubNotes
Machine Learning InterviewComprehensive ML interview preparation materials from FAANG, Snapchat, LinkedInGitHub LinkBlog: mlengineer.io
Cracking the Data Science InterviewCollection of cheatsheets, books, questions, and portfolio for DS/ML interview prepGitHub Link