amit1nayak

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

FDP-Lecture-PPT

Lectures PPT on Blockchain and Smart Contract Technology

forecasting

Time series modelling with sunspot data

GPT-App

The simplest, fastest repository for training/finetuning medium-sized GPTs.

GPT-from-scratch

Re-implementation of Andrej Karpathy's nanoGPT

GPT3_Beta

lime

Lime: Explaining the predictions of any machine learning classifier

Math-for-Data-Science

Required math subjects for data science.

pdfGPT

PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The only open source solution to turn your pdf files in a chatbot!

Skin-Cancer-Classification-using-Deep-Learning

Classify Skin cancer from the skin lesion images using Image classification. The dataset for the project is obtained from the Kaggle SIIM-ISIC-Melanoma-Classification competition.

amit1nayak/GPT-App

The simplest, fastest repository for training/finetuning medium-sized GPTs.

amit1nayak/pdfGPT

PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The only open source solution to turn your pdf files in a chatbot!

amit1nayak/5GNetwrokslicing

amit1nayak/AI-for-Good-Specialization

Learn AI's role in addressing complex challenges. Build skills combining human and machine intelligence for positive real-world impact using AI

amit1nayak/AI-Powered-5G-OpenRAN-Optimizer

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

amit1nayak/Building-Systems-with-the-ChatGPT-API

In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model.

amit1nayak/cover-agent

CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement! 💻🤖🧪🐞

amit1nayak/Functions-Tools-and-Agents-with-LangChain

You’ll explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

amit1nayak/generative-ai-for-beginners

12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

amit1nayak/Generative-AI-with-LLMs

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.

amit1nayak/How-Diffusion-Models-Work

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

amit1nayak/kb-voiceflow-demo

amit1nayak/LangChain-for-LLM-Application-Development

In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework.

amit1nayak/llm-agent-web-tools

A simple Google Search Engine Crawler.

amit1nayak/LLM-cookbook-RAG

amit1nayak/LLM-eval-survey

The official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models".

amit1nayak/LLM-PlayLab

This playlab encompasses a multitude of projects crafted through the utilization of Large Language Models, showcasing the versatility and impact of these models across various applications.

amit1nayak/LLM4Annotation

amit1nayak/ml-ferret

amit1nayak/ML-Papers-Explained

Explanation to key concepts in ML

amit1nayak/ML-Papers-of-the-Week

🔥Highlighting the top ML papers every week.

amit1nayak/pandas-ai

Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

amit1nayak/prismer

The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".

amit1nayak/R2R-RAG

The framework for fast development and deployment of RAG systems.

amit1nayak/rag-fusion

RAG-Fusion implementation using Langchain, Weaviate and OpenAI

amit1nayak/Scrapegraph-ai

Python scraper based on AI

amit1nayak/state-of-open-source-ai

Clarity in the current fast-paced mess of Open Source innovation

amit1nayak/taipy

Turns Data and AI algorithms into production-ready web applications in no time.

amit1nayak/Taiwanese-Whisper

fine-tune Whipser model for Taiwanese speech recognition

amit1nayak/tiny-transformer

Tiny transformer models implemented in pytorch.