Learning Resources
Curated resources to supplement your AI learning journey.
Free GPU Platforms
Google Colab
- Free Tier: 12-15 hours of GPU access per day
- GPU Types: T4, P100 (free tier), A100/V100 (Colab Pro)
- Best For: Quick experiments, tutorials, sharing notebooks
- Get Started →
Kaggle Notebooks
- Free Tier: 30 hours GPU per week, 20 hours TPU per week
- GPU Types: P100, T4
- Best For: Competitions, large datasets, longer training
- Get Started →
Comparison Table
| Feature | Google Colab Free | Kaggle Free | Colab Pro |
|---|---|---|---|
| GPU Hours | ~12hrs/day | 30hrs/week | ~24hrs/day |
| GPU Type | T4 | P100, T4 | A100, V100 |
| RAM | 12GB | 16GB | 32GB |
| Disk | 15GB | 20GB | 50GB |
| Cost | Free | Free | $10/month |
| Timeout | 12 hours | 9 hours | 24 hours |
Python Libraries
Core ML/DL Frameworks
- PyTorch: Documentation | Tutorials
- TensorFlow: Documentation | Guides
- Scikit-learn: Documentation | Examples
Specialized Libraries
- Hugging Face Transformers: Docs | Models
- OpenCV: Documentation | Tutorials
- NLTK: Documentation | Book
- spaCy: Documentation | Models
Data Processing
- NumPy: Documentation | Tutorials
- Pandas: Documentation | Getting Started
- Matplotlib: Documentation | Gallery
- Seaborn: Documentation | Examples
Datasets
Public Dataset Repositories
- Kaggle Datasets: Browse - Thousands of datasets with notebooks
- UCI ML Repository: Browse - Classic ML datasets
- HuggingFace Datasets: Browse - NLP and multimodal datasets
- Google Dataset Search: Search - Find datasets across the web
Recommended Datasets for Practice
- MNIST: Handwritten digits (beginner-friendly)
- CIFAR-10/100: Object classification
- ImageNet: Large-scale image classification
- COCO: Object detection and segmentation
- IMDb Reviews: Sentiment analysis
- WikiText: Language modeling
Research Papers
Must-Read Papers
- Attention Is All You Need - Original Transformer paper
- BERT - Bidirectional transformers
- GPT-3 - Large language models
- ResNet - Deep residual networks
- GAN - Generative adversarial networks
Paper Repositories
- Papers with Code - Papers + implementations
- arXiv.org - Preprint server
- Distill.pub - Interactive ML research
Video Courses
YouTube Channels
- 3Blue1Brown - Math visualizations
- StatQuest - ML concepts simplified
- Andrej Karpathy - Deep learning from scratch
- Two Minute Papers - Latest AI research
Free Online Courses
- Fast.ai - Practical deep learning
- Andrew Ng's ML Course - Stanford classic
- Deep Learning Specialization - Comprehensive DL course
Books (Free)
- Deep Learning Book by Goodfellow et al.
- Dive into Deep Learning - Interactive textbook
- Neural Networks and Deep Learning by Nielsen
- ML Engineering Book by Burkov
Communities
Discussion Forums
- r/MachineLearning - Research discussions
- r/learnmachinelearning - Beginner-friendly
- AI Skills Hub Discussions - Our community
Social
- Twitter/X: Follow #MachineLearning, #DeepLearning, #AI
- LinkedIn: Join ML groups and follow practitioners
- Discord: Many ML communities with study groups
Tools & Utilities
Development Tools
- Jupyter Notebook - Interactive coding
- VS Code - IDE with Python extensions
- Git - Version control
MLOps & Experiment Tracking
- Weights & Biases - Experiment tracking (free tier)
- MLflow - Open source ML platform
- DVC - Data version control
Model Deployment
Blogs to Follow
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