collection of books 48 laws of power, meditations, Atomic habits and many more

Tutorials on Big Data essentials: Hadoop, MapReduce, Spark.

[Video]Colab Notebooks for Python for Data Science by Pearson

Adding guardrails to large language models.

This is a workshop designed for Amazon Bedrock a foundational model service.

Generative-AI work🧠 💡📚

Using actions in NeMo Guardrails gives us the ability to do a lot of things without needing heavy agent decision making pipelines. We can enable to use of tools with little more than what is essent…

Config files for my GitHub profile.

Welcome to Build LLM Apps with LangChain, your gateway to creating powerful applications using Large Language Models (LLMs) powered by LangChain technology.

A collection of applications that can be used with Large Language Models (LLMs).

Master the art of designing and organizing AI agents. Learn to automate complex, multi-step business processes by creating specialized AI agent teams using the open-source library crewAI.

Modern DevOps Practices, published by Packt

The Deep Learning Architect’s Handbook, published by Packt

100+ Python challenging programming exercises

An example of how to show console output inside streamlit app.

Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories.

materials for learing various stuff by doing them myself

Knowledge Agents and Management in the Cloud

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Python Tutorials

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.