Yash Pratap Singh's starred repositories
generative-ai-for-beginners
18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
awesome-artificial-intelligence
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
StockChecker
A web-scraper that checks a URL for item stock status, sends out alert to your Telegram if found! Works with dynamic webpages as well.
system-design
Learn how to design systems at scale and prepare for system design interviews
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
awesome-mlops
A curated list of references for MLOps
DevOps-MLOps
Tools for DevOps and MLOps. Materials and projects. New technologies and infrastructure review.
mlflow-project-best-practices
An example MLFlow project
software-dev-for-mlops-101
Set up your local environment to do some real Machine Learning Operations software development, just like pro MLOps practitioners.
mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
mlops-zoomcamp
Free MLOps course from DataTalks.Club
mlp-regression-template
Example repo to kickstart integration with mlflow pipelines.
mlflow-workshop-part-1
Partly lecture and partly a hands-on tutorial and workshop, this is a three part series on how to get started with MLflow. In this three part series, we will cover MLflow Tracking, Projects, Models, and Model Registry.
Mubert-Text-to-Music
A simple notebook demonstrating prompt-based music generation via Mubert API
freeCodeCamp
freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.
the-book-of-secret-knowledge
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
ResourceBank_CV_NLP_MLOPS_2022
This repository offers a goldmine of materials for students of computer vision, natural language processing, and machine learning operations.
data-science-interviews
Data science interview questions and answers
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Data-Science-For-Beginners
10 Weeks, 20 Lessons, Data Science for All!
ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.
best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
handson-ml2
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.