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🦜🔗 Build context-aware reasoning applications
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Data Engineering Zoomcamp is a free nine-week course that covers the fundamentals of data engineering.
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.
This is a repo with links to everything you'd ever want to learn about data engineering
A guidance language for controlling large language models.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
Free MLOps course from DataTalks.Club
Official inference library for Mistral models
Learn ML engineering for free in 4 months!
An open-source, low-code machine learning library in Python
Technical Analysis Library using Pandas and Numpy
LLM Zoomcamp - a free online course about real-life applications of LLMs. In 10 weeks you will learn how to build an AI system that answers questions about your knowledge base.
Jupyter extensions that help you write code faster: Context aware AI Chat, Autocomplete, and Spreadsheet
Machine Learning Course, Sharif University of Technology
Learn Apache Spark in Scala, Python (PySpark) and R (SparkR) by building your own cluster with a JupyterLab interface on Docker. ⚡
A python package to access tsetmc data
🤗 ParsBERT: Transformer-based Model for Persian Language Understanding
This comprehensive, hands-on course provides a thorough exploration into the world of algorithmic trading, aimed at students, professionals, and enthusiasts with a basic understanding of Python pro…
Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
Persian Bert For Long-Range Sequences
Machine learing path for learning
POC of Digikala Semantic Search
Example lecture for Constraint Satisfaction Problems in an interactive jupyter notebook. With python code to solve CSPs, with visualization of Sudoku and NQueens problems.
