ML
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.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
A complete daily plan for studying to become a machine learning engineer.
Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
Compiled Notes for all 9 courses in the Coursera Data Science Specialization
Streamlit — A faster way to build and share data apps.
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Here you will find all the concepts related to Machine Learning.
This repo contains the Applied Ai Course Assignments and Notes.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
The guide to tackle with the Text Summarization
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and mo…
This is a repo of basic Machine Learning what I learn. More to go...
🧮 A collection of resources to learn mathematics for machine learning
This is Andrew NG Coursera Handwritten Notes.
Compilation of resources for aspiring data scientists
This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube
📈 A curated list of awesome data visualization libraries and resources.
A curated list of Machine learning videos, links, projects and datasets to help you conquer the ML landscape in 6 months