MUNIRAJA's starred repositories
start-machine-learning
A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Complete-Data-Analytics-with-Projects
This repository contains everything you need to become proficient in Data Analytics
Data-and-ML-Projects-
This repository contains projects covering Data Analytics, Data Science, Data Engineering, Machine Learning
handson-ml3
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.
Time-Series-Analysis-and-Forecasting
This repository contains everything you need to become proficient in Time Series Analysis and Forecasting
Grokking-Deep-Learning
this repository accompanies the book "Grokking Deep Learning"
awesome-llm-interpretability
A curated list of Large Language Model (LLM) Interpretability resources.
handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
tensorflow
An Open Source Machine Learning Framework for Everyone
Top-Deep-Learning
Top 200 deep learning Github repositories sorted by the number of stars.
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
ML-Course-Notes
🎓 Sharing machine learning course / lecture notes.
ML-Papers-Explained
Explanation to key concepts in ML
ML-Papers-of-the-Week
🔥Highlighting the top ML papers every week.
Prompt-Engineering-Guide
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
GNNs-Recipe
🟠 A study guide to learn about Graph Neural Networks (GNNs)
uncertain_ground_truth
Dermatology ddx dataset, Jax implementations of Monte Carlo conformal prediction, plausibility regions and statistical annotation aggregation from our recent work on uncertain ground truth (TMLR'23 and ArXiv pre-print).
mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.