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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
An open-source RAG-based tool for chatting with your documents.
Questions? Contact me at @DhruvAtreja1
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Search plugins for the search feature
Collection of awesome LLM apps with RAG using OpenAI, Anthropic, Gemini and opensource models.
Access large language models from the command-line
📚 Freely available programming books
A curated awesome list of lists of interview questions. Feel free to contribute! 🎓
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Everything you need to prepare for your technical interview
All Algorithms implemented in Python
💯 Curated coding interview preparation materials for busy software engineers
A simple personal Bitcoin block explorer
A resource to help you pass system design interview and become good at work 👇
Unified framework for building enterprise RAG pipelines with small, specialized models
Panel: The powerful data exploration & web app framework for Python
This is a repo with links to everything you'd ever want to learn about data engineering
Learn Low Level Design (LLD) and prepare for interviews using free resources.
List of Computer Science courses with video lectures.
Standard and Advanced Demos for learn.cantrill.io courses
Bitcoin Model is an open-source model designed to simulate long-range outcomes of various Bitcoin strategies tailored for individuals, corporations, institutions, and nation-states. Users can input…
Code for the "Build Your Own Search Engine" workshop
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Learn ML engineering for free in 4 months!
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all