Learning Resources
Deep Learning & CV
Data & Business Intelligence
DeepLearning.AI
Specialized Topics
Web Development
Career Resources
📚 Excellent Learning Resources
🌱 Fundamental Deep Learning
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Physics Informed Machine Learning | Application 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 Transformers | GitHub Link | Transformer Notes |
| All about Deep Learning | Comprehensive repo covering NLP, Tensorflow, Pytorch, and recommendation systems | GitHub Link | |
| A collection of various DL models (Sebastian Raschka) | Collection of DL architectures, implementations, and practical tips | GitHub Link | |
| Deep Learning from Scratch | Implementation of deep learning algorithms from first principles | GitHub Link | Book |
👁️ Computer Vision
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Computer Vision Engineer Channel | Comprehensive tutorials from basics (YOLO, tracking, pose estimation) to advanced SAAS web apps | - | YouTube Channel |
| PyTorch Image Models (timm) | Collection of SOTA computer vision models and training scripts | GitHub Link | |
| Object Detection Series | In-depth implementation of various object detection algorithms | GitHub Link | YouTube Playlist |
| Variational AutoEncoder | Variational AutoEncoder Paper and Code From Scratch | GitHubt Repo | 1. YouTube Variational AutoEncoder Paper Walkthrough 2. YouTube Variational Autoencoder from scratch in PyTorch |
| U-NET | U-NET Paper and Code From Scratch | GitHubt Repo | 1. YouTube U-NET Paper Walkthrough 2. PyTorch Image Segmentation Tutorial with U-NET from scratch |
| EfficientNet | EfficientNet Paper and Code From Scratch | GitHubt Repo | 1. YouTube EfficientNet Paper Walkthrough 2. EfficientNet from scratch in Pytorch |
| Generative Adversarial Networks (GANs) | Implementation of various GAN architectures | GitHub Link | YouTube Playlist |
| Variational Autoencoder from scratch | PyTorch implementation of VAE with detailed explanation | GitHub Link | YouTube Tutorial |
| Variational Autoencoders (VAE) in PyTorch | Extensive collection of VAE models implemented in PyTorch | GitHub Link | |
| VAE From Scratch Explained | Complete walkthrough of VAE theory and implementation | GitHub Link | YouTube Tutorial |
| simpleVAE for MNIST | Train VAE on CPU with latent space visualization and number interpolation | GitHub Link | YouTube Tutorial |
| Denoising Diffusion Models | Implementation of DDPM with training and sampling, mimicking Stable Diffusion architecture | GitHub Link | YouTube Tutorial |
| Stable Diffusion in PyTorch | PyTorch implementation of Stable Diffusion | GitHub Link | YouTube Tutorial |
| Vision Transformers from Scratch | Implementation of Vision Transformers (ViT) with detailed explanations | GitHub Link | YouTube Tutorial |
🗣️ Natural Language Processing (NLP) & 🤖 Large Language Models (LLMs)
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| BERT from Scratch | Implementation of BERT in PyTorch and TensorFlow | GitHub Link | |
| DeepSeek-R1 from Scratch | Implementing a smaller model inspired by DeepSeek-R1 | GitHub Link | Blog (Zhihu) |
| NLP from Scratch with PyTorch | Comprehensive guide to building NLP models with PyTorch | GitHub Link | |
| Build LLM Applications from Scratch (Stanford) | Course and companion book for LLM application building | GitHub Link | Companion book in repo |
| Build an LLM from Scratch (Sebastian Raschka) | Step-by-step LLM building, fine-tuning, and practical examples | GitHub Link | Book, Video Playlist |
| 4-hour LLM Coding Workshop | Comprehensive LLM coding workshop by Sebastian Raschka | GitHub Link | YouTube |
| LLM Lectures by Sebastian Raschka | Comprehensive lectures covering multiple LLM topics | GitHub Link | YouTube Playlist |
| The Illustrated Transformer | Visual guide to understanding transformer architecture | Blog |
🔍 LLM Applications
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Neo4j-Labs Text2Cypher | Collection of datasets, evaluation scripts, and fine-tuning instructions for Text2Cypher models | GitHub Link | Includes notebooks for evaluating LLMs on the provided datasets |
| Neo4j Text2Cypher (2024) Dataset | Comprehensive dataset for training and evaluating text-to-Cypher conversion models | GitHub Link | Blog Post |
| Fine-tuning LLM for Cypher Generation with H2O | Guide to fine-tuning an LLM model with H2O LLM Studio to generate Cypher statements | GitHub Link | Blog Post |
| Cypher Generation - The Good, The Bad, and The Messy | Methods for creating fine-tuning datasets for text-to-Cypher generation | GitHub Link | Blog Post |
| Neo4j Text2Cypher - Natural Language Queries | Guide to implementing natural language queries with Neo4j Text2Cypher | - | Neo4j Labs Guide |
| Neo4j GraphRAG Text2Cypher Source Code | Source code for the text2cypher retriever in Neo4j’s GraphRAG module |
- | Neo4j Documentation |
| RetailBanking-Conversations | Dataset with 320 realistic banking dialogues for LLM training in financial domain | HuggingFace Dataset | Created with WizardSData tool for synthetic datasets |
| Knowledge Graph-based LLM Dialogue System | Complete system with data preprocessing, graph construction, graph completion, dialogue model, and web interface | GitHub Link | |
| WizardSData | Python library for generating synthetic conversation datasets for fine-tuning models, especially for regulated sectors | GitHub Link | Configurable roles, conversation length, temperature settings; created by Pere Martra |
📈 MLOps & Explainable ML & Efficient ML
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| MLOps Basics | Fundamental concepts, implementation of MLOps pipelines | GitHub Link | |
| Explainable ML | Techniques and implementation for explainable machine learning | - | YouTube Playlist |
| MLOps Zoomcamp | Comprehensive course on MLOps practices and implementation | GitHub Link | YouTube Course |
| Text Generation API | Lightweight FastAPI service for AI-powered text generation | GitHub Link | Mini project showcasing Dockerization, RESTful API, and containerization |
| MLOps by Coursera | Coursera Course on ML in Production | GitHub Link | Course |
| Efficient ML by Prof Han Song | EfficientML.ai course from MIT | GitHub Link (2023 Fall) | 1 - Course website (2024 Fall), Youtube (2024 Fall), 2 - Course website (2023 Fall) |
🎵 Audio Processing & Music Generation
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Audio Signal Processing for ML | Audio processing techniques tailored for machine learning tasks | GitHub Link | YouTube Playlist |
| Audio Data Augmentation | Comprehensive tutorial on audio data augmentation methods | GitHub Link | YouTube |
| Generating Sound with Neural Networks | Neural methods for audio synthesis | GitHub Link | YouTube Playlist |
| Melody Generation with RNN-LSTM | Music generation using RNN and LSTM models | GitHub Link | YouTube Playlist |
| AudioCraft by Meta | Framework for audio generation including MusicGen, AudioGen, and EnCodec | GitHub Link | Meta AI Blog |
🎤 Text-to-Speech & Voice Cloning
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Text to Speech and Voice Cloning | Comprehensive course covering TTS fundamentals and voice cloning techniques | GitHub Link | YouTube Playlist |
📊 Graph Data Science & Visualization
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Stanford CS224W: ML with Graphs | Stanford’s comprehensive course on graph machine learning | GitHub 1, GitHub 2, GitHub 3 | YouTube Playlist |
| Graph Convolutional Network (GCN) Explained | Clear explanation and implementation of GCN | GitHub Link | YouTube Tutorial |
| 15 Best Graph Visualization Tools | Tools for Neo4j graph visualization | - | Blog Post |
| PyG (PyTorch Geometric) | Library for deep learning on irregular structures like graphs | GitHub Link | Documentation |
| Awesome Explainable Graph Reasoning | Collection of research papers and software for explainability in graph ML | GitHub Link |
💾 Data Engineering & Business Intelligence
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| DataTalksClub Data Engineering Zoomcamp | Free 9-week course teaching data engineering fundamentals by building an end-to-end pipeline from scratch | GitHub Link | YouTube Playlist |
| Apache Spark with Databricks Projects | Collection of end-to-end projects using PySpark and Databricks for beginners | GitHub Link | Medium Post |
| Databricks & Spark Tutorials Repository | Beginner-focused repo covering PySpark and Spark SQL basics on Databricks | GitHub Link | Structured like a course targeting the Databricks Data Engineer certification |
| Databricks Tutorial (From Zero to Hero) by Ansh Lamba | 4-hour comprehensive tutorial on Azure Databricks | GitHub Link | YouTube |
| Azure Databricks End-To-End Data Engineering Project (From Scratch!) by Ansh Lamba | 4-hour projects on Azure Databricks | GitHub Link | YouTube |
| PySpark Full Course (From Zero to Pro!) by Ansh Lamba | 6-hour comprehensive tutorial on PySpark | GitHub Link | YouTube |
| Microsoft Learn - Azure Databricks | Official interactive learning module for Azure Databricks fundamentals | - | MS Learn |
| Implement a Data Lakehouse on Azure | Learning path for building lakehouse solutions with Azure Databricks | - | MS Learn |
| Master Databricks and Apache Spark | Comprehensive playlist covering Databricks platform and Spark fundamentals | - | YouTube Playlist |
| Power BI Tutorial - Beginner to Pro | 4-hours Comprehensive hands-on Power BI tutorial with step-by-step walkthrough | - | YouTube (2023), YouTube (2024) |
| Power BI Full Course Tutorial | 8+ hours of Power BI training covering basics to advanced concepts | Exercise File | YouTube |
| Power BI Tutorial for Beginners to Advanced | 20-hour free Power BI course covering all aspects | GitHub | YouTube 1, Youtube Video 2, Medium post |
| Tableau Ultimate Full Course | Extremely comprehensive 21-hour Tableau course from zero to advanced | - | YouTube |
| Tableau Full Course 2025 | 5-hour accelerated tutorial covering Tableau basics | - | YouTube Playlist |
| Master Using SQL with Python Full Course | In-depth course on integrating SQL with Python for data engineering tasks | - | YouTube Playlist |
🧠 DeepLearning.AI Courses & Projects
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| LangChain for LLM Application Development | Foundation course for building LLM-powered applications | GitHub Link | DeepLearning.ai Course |
| LangChain Chat with Your Data | Learn to build RAG applications to chat with your private data | GitHub Link | DeepLearning.ai Course |
| Functions, Tools, and Agents with LangChain | Building intelligent agents with function calling capabilities | GitHub Link | DeepLearning.ai Course |
| AI Agents in LangGraph | Creating multi-agent systems with LangGraph | GitHub Link | DeepLearning.ai Course |
| Long-Term Agentic Memory with LangGraph | Implementing persistent memory for AI agents | GitHub Link | DeepLearning.ai Course |
| AI Agentic Design Patterns with AutoGen | Building complex agent architectures with Microsoft’s AutoGen | GitHub Link | DeepLearning.ai Course |
| Pretraining LLMs | Understanding how large language models are pretrained | GitHub Link, GitHub 2 | DeepLearning.ai Course |
| MCP: Build Rich-Context AI Apps with Anthropic | Learn to build context-aware AI applications using Model Context Protocol | - | DeepLearning.ai Course |
💰 AI & Quantitative Finance
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| AI Quant Learning | Comprehensive systematic learning on quantitative trading strategies | GitHub Link | YouTube Playlist |
| LLMs in Finance by Hanane Dupouy | Practical generative AI and AI agents in finance | GitHub Link | |
| Financial Fraud Detection Using LLMs | Comparing FinBERT and GPT-2 against traditional ML for fraud detection | GitHub Link | Blog |
| Financial Analysis with LLM | NLP application for financial document analysis, detecting suspicious patterns and ML/TF activities | GitHub Link | |
| FinRL | Deep reinforcement learning framework for financial applications | GitHub Link | Documentation |
| FinLLMOpt | Optimized LLMs for financial applications including Llama-FinSent-S (pruned LLaMA-3.2-1B) for financial sentiment analysis | GitHub Link | 26% smaller, 50% better instruction-following, 400% better multi-step reasoning |
| Awesome Fraud Detection Papers | Curated list of data mining papers for fraud detection | GitHub Link |
⚛️ Front-end Development
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| HTML & CSS Full Course | Web development fundamentals for beginners, covering HTML structure and CSS styling | GitHub Link | YouTube |
| JavaScript Beginner Course | Foundation course covering JavaScript basics for web development | GitHub Link | YouTube |
| React JS Full Course 2024 | Comprehensive course covering React fundamentals, hooks, context API, and routing | GitHub Link | YouTube |
| React.JS Full Course - Build 4 Projects | Project-based course building four applications to reinforce state management and API integration | GitHub Link | YouTube |
| Learn React JS - Full Beginner’s Tutorial & Practice Projects | Project-based course building four applications to reinforce state management and API integration | GitHub Link | YouTube |
🎯 Machine Learning Interview Preparation
| Resource Name | Description | GitHub | Notes |
|---|---|---|---|
| Machine Learning Interview | Comprehensive ML interview preparation materials from FAANG, Snapchat, LinkedIn | GitHub Link | Blog: mlengineer.io |
| Cracking the Data Science Interview | Collection of cheatsheets, books, questions, and portfolio for DS/ML interview prep | GitHub Link |