Generative AI Indepth Basic to Advance is a repository focused on providing tutorials and resources related to generative artificial intelligence. The repository covers a wide range of topics from basic concepts to advanced techniques in the field of generative AI. Users can find detailed explanations, code examples, and practical demonstrations to help them understand and implement generative AI algorithms. The goal of this repository is to help beginners get started with generative AI and to provide valuable insights for more experienced practitioners.

The ai-workshop-code repository contains code examples and tutorials for various artificial intelligence concepts and algorithms. It serves as a practical resource for individuals looking to learn and implement AI techniques in their projects. The repository covers a wide range of topics, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. By exploring the code and following the tutorials, users can gain hands-on experience with AI technologies and enhance their understanding of how these algorithms work in practice.

LLMs-playground is a repository containing code examples and tutorials for learning and experimenting with Large Language Models (LLMs). It provides a hands-on approach to understanding how LLMs work and how to fine-tune them for specific tasks. The repository covers various LLM architectures, pre-training techniques, and fine-tuning strategies, making it a valuable resource for researchers, students, and practitioners interested in natural language processing and machine learning. By exploring the code and following the tutorials, users can gain practical insights into working with LLMs and apply their knowledge to real-world projects.

AI-Learning is a free e-book for neural network/deep learning teaching. In the first volume, you will initially learn about neural networks, deeply understand its essence and design principles, and improve it accordingly, ultimately putting it into simple practice. The book supports bilingual practice in JS/C++, equipped with a massive interactive Geogebra mathematical animation demonstration to help you learn neural networks in a simple and profound way. Join us for discussions and suggestions for modifications.

The ai-collection repository is a collection of various artificial intelligence projects and tools aimed at helping developers and researchers in the field of AI. It includes implementations of popular AI algorithms, datasets for training machine learning models, and resources for learning AI concepts. The repository serves as a valuable resource for anyone interested in exploring the applications of artificial intelligence in different domains.

This repository contains a collection of AI algorithms and models for various machine learning tasks. It provides implementations of popular algorithms such as neural networks, decision trees, and support vector machines. The code is well-documented and easy to understand, making it suitable for both beginners and experienced developers. The repository also includes example datasets and tutorials to help users get started with building and training AI models. Whether you are a student learning about AI or a professional working on machine learning projects, this repository can be a valuable resource for your development journey.

Generative-AI-Scratch-2-Advance-By-ThatAIGuy is a repository that provides advanced resources and tools for individuals interested in exploring generative AI techniques from scratch. It offers a comprehensive guide and hands-on projects to help users advance their understanding of generative AI algorithms and applications. The repository includes detailed tutorials, code samples, and datasets to support learners in building their own generative AI models and projects. Whether you are a beginner looking to dive into generative AI or an experienced practitioner seeking to enhance your skills, Generative-AI-Scratch-2-Advance-By-ThatAIGuy is a valuable resource to support your learning journey.

This repository provides a step-by-step guide for building your own machine learning models from scratch. It covers various machine learning algorithms and techniques, including linear regression, logistic regression, decision trees, and neural networks. The code examples are written in Python and include detailed explanations to help beginners understand the concepts behind machine learning. By following the tutorials in this repository, you can gain a deeper understanding of how machine learning works and develop your own models for different applications.

This repository serves as an archive for computer science learning notes, codes, and materials. It covers a wide range of topics including basic knowledge, AI, backend & big data, tools, and other related areas. The content is organized into sections and subsections for easy navigation and reference. Users can find learning resources, programming practices, and tutorials on various subjects such as languages, data structures & algorithms, AI, frameworks, databases, development tools, and more. The repository aims to support self-learning and skill development in the field of computer science.

A drill of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. This repository is designed for individuals aiming to excel in the field of Data and AI, providing video sessions and text content for learning. It caters to those in leadership positions, professionals, and students, emphasizing the need for dedicated effort to achieve excellence in the tech field. The content covers various topics with a focus on practical application.

Spring AI Examples is a repository containing various examples of integrating artificial intelligence capabilities into Spring applications. The examples cover a wide range of AI technologies such as machine learning, natural language processing, computer vision, and more. These examples serve as a practical guide for developers looking to incorporate AI functionalities into their Spring projects.

LemonAI is a versatile machine learning library designed to simplify the process of building and deploying AI models. It provides a wide range of tools and algorithms for data preprocessing, model training, and evaluation. With LemonAI, users can easily experiment with different machine learning techniques and optimize their models for various tasks. The library is well-documented and beginner-friendly, making it suitable for both novice and experienced data scientists. LemonAI aims to streamline the development of AI applications and empower users to create innovative solutions using state-of-the-art machine learning methods.

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on Applied Generative AI Fundamentals. It covers prompt engineering, developing custom GPTs, and Multi AI Agent Systems. The course helps in building a strong understanding of generative AI, applying Large Language Models (LLMs) and diffusion models practically. It introduces principles of prompt engineering to work efficiently with AI, creating custom AI models and GPTs using OpenAI, Azure, and Google technologies. It also utilizes open source libraries like LangChain, CrewAI, and LangGraph to automate tasks and business processes.

This code repository is for the book 'Mastering NLP from Foundations to LLMs', which provides an in-depth introduction to Natural Language Processing (NLP) techniques. It covers mathematical foundations of machine learning, advanced NLP applications such as large language models (LLMs) and AI applications, as well as practical skills for working on real-world NLP business problems. The book includes Python code samples and expert insights into current and future trends in NLP.

Model Mondays is a repository dedicated to providing a collection of machine learning models implemented in Python. It aims to serve as a resource for individuals looking to explore and experiment with various machine learning algorithms and techniques. The repository includes a wide range of models, from simple linear regression to complex deep learning architectures, along with detailed documentation and examples to facilitate learning and understanding. Whether you are a beginner looking to get started with machine learning or an experienced practitioner seeking reference implementations, Model Mondays offers a valuable repository of models to study and leverage in your projects.

GenAiGuidebook is a comprehensive resource for individuals looking to begin their journey in GenAI. It serves as a detailed guide providing insights, tips, and information on various aspects of GenAI technology. The guidebook covers a wide range of topics, including introductory concepts, practical applications, and best practices in the field of GenAI. Whether you are a beginner or an experienced professional, this resource aims to enhance your understanding and proficiency in GenAI.

This repo collects AI-related utilities. ## All Categories * All Categories * ChatGPT and other closed-source LLMs * AI Search engine * Open Source LLMs * GPT/LLMs Applications * LLM training platform * Applications that integrate multiple LLMs * AI Agent * Writing * Programming Development * Translation * AI Conversation or AI Voice Conversation * Image Creation * Speech Recognition * Text To Speech * Voice Processing * AI generated music or sound effects * Speech translation * Video Creation * Video Content Summary * OCR(Optical Character Recognition)

NSMusicS is a local music software that is expected to support multiple platforms with AI capabilities and multimodal features. The goal of NSMusicS is to integrate various functions (such as artificial intelligence, streaming, music library management, cross platform, etc.), which can be understood as similar to Navidrome but with more features than Navidrome. It wants to become a plugin integrated application that can almost have all music functions.

biniou is a self-hosted webui for various GenAI (generative artificial intelligence) tasks. It allows users to generate multimedia content using AI models and chatbots on their own computer, even without a dedicated GPU. The tool can work offline once deployed and required models are downloaded. It offers a wide range of features for text, image, audio, video, and 3D object generation and modification. Users can easily manage the tool through a control panel within the webui, with support for various operating systems and CUDA optimization. biniou is powered by Huggingface and Gradio, providing a cross-platform solution for AI content generation.

Generative AI JS is a JavaScript library that provides tools for creating generative art and music using artificial intelligence techniques. It allows users to generate unique and creative content by leveraging machine learning models. The library includes functions for generating images, music, and text based on user input and preferences. With Generative AI JS, users can explore the intersection of art and technology, experiment with different creative processes, and create dynamic and interactive content for various applications.

The 'pictureChange' repository is a plugin that supports image processing using Baidu AI, stable diffusion webui, and suno music composition AI. It also allows for file summarization and image summarization using AI. The plugin supports various stable diffusion models, administrator control over group chat features, concurrent control, and custom templates for image and text generation. It can be deployed on WeChat enterprise accounts, personal accounts, and public accounts.

Generative AI Indepth Basic to Advance is a repository focused on providing tutorials and resources related to generative artificial intelligence. The repository covers a wide range of topics from basic concepts to advanced techniques in the field of generative AI. Users can find detailed explanations, code examples, and practical demonstrations to help them understand and implement generative AI algorithms. The goal of this repository is to help beginners get started with generative AI and to provide valuable insights for more experienced practitioners.

NodeTool is a platform designed for AI enthusiasts, developers, and creators, providing a visual interface to access a variety of AI tools and models. It simplifies access to advanced AI technologies, offering resources for content creation, data analysis, automation, and more. With features like a visual editor, seamless integration with leading AI platforms, model manager, and API integration, NodeTool caters to both newcomers and experienced users in the AI field.

The ai-enhanced-audio-book repository contains AI-enhanced audio plugins developed using C++, JUCE, libtorch, RTNeural, and other libraries. It showcases neural networks learning to emulate guitar amplifiers through waveforms. Users can visit the official website for more information and obtain a copy of the book from the publisher Taylor and Francis/ Routledge/ Focal.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.