A roadmap for getting started with Machine Learning
A "production-ready" simple project template to quickly start an Artificial Intelligence (AI), Machine Learning (ML) and/or Data Science (DS) project with basic files, branches and directory structure.
Beginner → Intermediate (Student & Self-Learner Friendly)
Welcome to the Machine Learning Roadmap! This comprehensive guide will take you from the basics to becoming proficient in machine learning. Whether you're a beginner or looking to expand your skills, this roadmap will provide you with a structured path to follow.
A structured hands-on journey to master PyTorch and Deep Learning through practical notebooks, exercises, and real-world AI projects.
The foundations of ML, built from scratch — one notebook at a time. NumPy → Pandas → Visualization → Statistics → ML → Deep Learning.
A collection of machine learning projects, programs and papers
14.9M-trip analytics platform with Python, PostgreSQL, dbt, data quality, and Tableau.
Темы из математики, которые нужны в Data Science: статистика, вероятность, линейная алгебра, математический анализ, оптимизация и метрики ML. Roadmap по математике для Data Science, Machine Learning и Deep Learning
A curated collection of key research papers and resources on LLMs and deep learning, organized by topic to provide a clear learning path from fundamentals to advanced techniques.
🚀 AI & Machine Learning Roadmap | Beginner to Advanced | Projects, Notes, and Resources to Master AI 🔥
Week 3 of my AI/ML learning journey. Focused on math foundations with NumPy and Matplotlib — including matrix multiplication, vector operations, statistics, and data visualization.
An end-to-end Machine Learning Engineering roadmap. Master the mathematical foundations, big data engineering, deep learning architectures, and production MLOps deployments from scratch.
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