Your ML & AI toolkit
Foundation models, deep learning, NLP, computer vision, GenAI development, and MLOps. From first neural network to production-grade ML systems.
Foundations & Courses
Top-down practical deep learning course. Build real models before diving into math. Best starting point for ML practitioners.
Visit →Andrew Ng's foundational ML and deep learning courses. Industry-standard credential across 5 courses.
Visit →Full Stanford Machine Learning course lecture notes, slides, and problem sets — publicly available.
Visit →Zero-to-hero neural network series building GPT from scratch. Best technical ML content on YouTube.
Visit →Google's 15-hour crash course with TensorFlow exercises, covering regression, classification, and neural nets.
Visit →The canonical graduate ML textbook by Hastie, Tibshirani, and Friedman. Free PDF from Stanford.
Visit →Frameworks & Libraries
Meta's dynamic computation graph framework. Dominant in research. Essential for custom model architectures.
Visit →Model hub with 500,000+ pretrained models. Transformers, Diffusers, Datasets, and Spaces — all free.
Visit →The go-to Python library for classical ML — pipelines, cross-validation, preprocessing, and 50+ algorithms.
Visit →Gradient boosted trees library. Wins Kaggle tabular competitions. Production-grade with GPU support.
Visit →Google's ML framework. Keras high-level API makes training and deployment straightforward.
Visit →Cross-platform inference engine. Run models trained in any framework with optimized performance.
Visit →Generative AI & LLMs
Framework for building LLM-powered applications with chains, agents, memory, and RAG pipelines.
Visit →Data framework for LLM applications. Best-in-class for RAG over custom knowledge bases.
Visit →Run Llama 3, Mistral, Gemma, and other open-source LLMs locally. Zero API cost for prototyping.
Visit →Ultra-fast LLM inference API with generous free tier. Llama 3, Mixtral, and Gemma available.
Visit →Build with Gemini models via free API access. Includes multimodal (text, image, audio) capabilities.
Visit →LLM prompt management, evaluation, and deployment platform. Great for iterating on production prompts.
Visit →MLOps & Experiment Tracking
Open-source MLOps platform for experiment tracking, model registry, and deployment. Self-hostable.
Visit →Experiment tracking, artifact versioning, and model performance dashboards. Free for individual use.
Visit →Git extension for versioning ML datasets and models. Integrates with GitHub and cloud storage.
Visit →GitHub-like platform for ML projects integrating DVC, MLflow, and LabelStudio in one place.
Visit →Build, ship, and scale AI applications. Unified model packaging and deployment to any cloud.
Visit →Fully managed MLOps platform on Google Cloud. Free tier covers Workbench notebooks and basic training.
Visit →Sector Applications
NLP & Text
Industrial-strength NLP library for tokenization, NER, dependency parsing, and text classification.
Visit →Python NLP toolkit for tokenization, stemming, tagging, parsing, and corpora access.
Visit →Compute dense sentence embeddings for semantic search, clustering, and similarity tasks.
Visit →Computer Vision
Dataset management, annotation, augmentation, and deployment for computer vision projects.
Visit →Industry standard library for real-time image and video processing in Python and C++.
Visit →Real-time object detection. YOLOv8 and YOLOv11 are best-in-class for speed vs. accuracy tradeoff.
Visit →Certifications
Google-issued certificate for building TensorFlow models across NLP, computer vision, and sequences.
Visit →AWS specialty certification for ML model training, tuning, and deployment on SageMaker.
Visit →4-course specialization covering feature engineering, model deployment, and ML pipelines in production.
Visit →Official Hugging Face course covering Transformers, fine-tuning, and building NLP pipelines end-to-end.
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