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This notebook is for all of my End to End Data Science personal project start from project overview, data collection, data processing, data visualization, machine learning modelling, NLP, and lastl…
This Repository Contain All the Artificial Intelligence Projects such as Machine Learning, Deep Learning and Generative AI that I have done while understanding Advanced Techniques & Concepts.
VIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models
Learn System Design concepts and prepare for interviews using free resources.
A Big Picture, Thesaurus, and Taxonomy of Modern JavaScript Web Development
🤔Notes for common front-end / full-stack problems in interviews. Covers common algorithms implementation in JavaScript, design patterns, JavaScript basics, Node.js basics, React/Redux basics, ES6 n…
🎤 Prepare for the interviews and sum up the most popular interview problems for front-end(HTML/CSS/Javascript), Web development, full-stack. Also did some typical coding practice questions, such as…
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.
The "Python Machine Learning (3rd edition)" book code repository
Master programming by recreating your favorite technologies from scratch.
WorldWise is a React application that allows users to explore cities from around the world.
Notebooks and code for the book "Introduction to Machine Learning with Python"
📚 Learn ML with clean code, simplified math and illustrative visuals. As you learn, work on interesting projects and share them on https://madewithml.com for the community to discover and learn from!
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
A collection of New Grad full time roles in SWE, Quant, and PM.
Kkight0 / docker-python
Forked from Kaggle/docker-pythonKaggle Python docker image
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Multi-user server for Jupyter notebooks