Research & Education

Technical_Book_DL is a comprehensive technical book on deep learning, offering a pedagogical approach to understanding the three most common neural network architectures: Feedforward, Convolutional, and Recurrent. For each architecture, the book meticulously details its fundamental building blocks. It then proceeds to derive the forward pass and the complete update rules for the backpropagation algorithm, providing a thorough understanding for students and AI enthusiasts. The entire document is available as a downloadable PDF, with all figures and LaTeX source files also provided in the repository for compilation. This resource is particularly valuable for those who prefer detailed, indexed formulas over abstract matrix formulations, ensuring a precise grasp of the underlying mechanics.

stanford_dl_ex is a repository offering programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial. It provides starter code designed to help users engage with and practice the concepts taught in the official Stanford tutorial, available at ufldl.stanford.edu/tutorial. This resource is particularly useful for individuals looking to deepen their understanding and practical application of deep learning principles through hands-on coding. The repository includes various modules covering different aspects of deep learning, such as convolutional neural networks (CNN), principal component analysis (PCA), and sparse autoencoders (STL). It serves as a valuable, free educational tool for students and researchers alike.

Top-Deep-Learning is an open-source project that compiles and ranks the top 200 deep learning GitHub repositories. The list is meticulously sorted by the number of stars each repository has received, offering a clear indicator of popularity and community engagement. This resource is invaluable for anyone looking to explore the most influential and actively developed projects within the deep learning domain. It is regularly updated to ensure the information remains current, reflecting the dynamic nature of deep learning research and development. The project's methodology involves querying the GitHub search API using terms like 'deep-learning', 'CNN', 'RNN', 'convolutional neural network', and 'recurrent neural network' to gather comprehensive results.

TensorKart is an open-source project that demonstrates self-driving capabilities within the classic game MarioKart 64, powered by Google's TensorFlow framework. Users can train a deep learning model by recording their own gameplay, which then learns to control the in-game kart. The model can generalize to new tracks even with a relatively small training dataset, as shown by its ability to drive on Royal Raceway after training on other tracks. The project provides scripts for recording gameplay samples, preparing training data, training the model with GPU acceleration (using cuDNN), and playing the game with the trained AI agent. It also includes features for overriding AI control with a joystick and outlines future work like reinforcement learning integration to improve performance based on lap times.

Türkçe Yapay Zeka Kaynakları is a comprehensive, open-source repository dedicated to deep learning and machine learning resources available in Turkish. Supported by the Deep Learning Türkiye community, this platform centralizes a wide array of materials including blog posts, video lectures, scientific articles, code examples, and datasets. It serves as an invaluable hub for individuals seeking to learn or conduct research in AI within the Turkish language. The resource is continuously updated and encourages contributions from the community, ensuring a rich and current collection of information across various AI topics, algorithms, frameworks, and applications.

text-generation-webui-colab offers a convenient Gradio web user interface for deploying and interacting with Large Language Models (LLMs) directly within a Google Colab environment. This open-source project supports a wide range of LLMs, including popular models like Llama 2, Vicuna, Falcon, and Mistral, often with GPTQ 4-bit quantization for efficient use. It's particularly useful for researchers, developers, and enthusiasts who want to experiment with different LLMs without extensive local setup. The repository provides numerous Colab notebooks pre-configured for specific models, simplifying the process of getting started with text generation, instruction following, and other LLM-based tasks.

ChatGPT for YouTube is a free Chrome Extension designed to provide instant, AI-generated summaries of YouTube videos. This tool eliminates the need for an AI account or API key, making it accessible for all users. It helps you quickly understand the main points of any YouTube video, significantly saving time and enhancing your learning experience. The extension offers a free tier with 7 summary quotas per week, and users can purchase additional quotas or subscribe to a Pro version for unlimited summaries and transcription words. It's an ideal solution for anyone looking to efficiently consume video content.

yt-channels-DS-AI-ML-CS is a comprehensive, open-source GitHub repository curating over 180 YouTube channels dedicated to Data Science, Data Engineering, Machine Learning, Deep Learning, Artificial Intelligence, Computer Science, programming, and software engineering. This resource is designed to help individuals easily discover educational content and stay updated with the latest trends and tutorials in these rapidly evolving fields. The list is categorized by topic, including Data Science/Analysis, ML/AI/DL, Data Engineering, Statistics/Math, AI research, Programming, Web-dev, Software Engineering, and more, making it simple to navigate and find relevant channels. Users are encouraged to contribute to the list by submitting pull requests, fostering a community-driven approach to knowledge sharing.

Heuris is an AI-powered learning platform designed to make complex subjects accessible through short, engaging 5-minute sessions. It covers a wide range of topics including History, Art, Economics, and Philosophy. The platform leverages AI conversations to guide users through their learning journey, adapting to individual interests and helping to explore new concepts effectively. This approach makes learning efficient and personalized, catering to individuals who enjoy self-directed exploration and quick, digestible content. Heuris aims to provide an interactive and adaptive educational experience for those looking to expand their knowledge in various academic and cultural fields.

Practici simplifies the learning journey by transforming PDFs into interactive test questions with powerful AI integration. Tailored for students and teachers, this platform fosters efficient studying, enabling seamless practice and better retention. Users can convert PDFs into interactive test questions, with the AI scanning documents, identifying key concepts, and generating multiple question types such as multiple-choice and fill-in-the-blanks. The platform also offers a free flashcard generator and allows users to customize, edit, and fine-tune the AI-generated content. Practici is mobile-friendly and accessible on all devices, making it a versatile tool for educational purposes.

Pixel Arcade Studio is a browser-based game studio where children can create their own games by giving instructions to AI, eliminating the need for coding. Designed with safety in mind, it provides a secure environment for kids to explore AI-assisted creation and develop meaningful projects quickly. The platform focuses on guided AI use with built-in safety guardrails, parent controls for under-13 creators, and an ad-free experience. It aims to replace multiple apps for game creation and AI exploration, offering a clear path from idea to playable game. The studio is suitable for families seeking creative screen time, teens and adults prototyping game ideas, and anyone looking for a safe way to engage with AI-assisted creation.

Write2Learn is an efficient English vocabulary learning tool designed to significantly enhance language proficiency. It immerses users in real-life contexts through interactive dialogues, helping them understand word usage in various situations. The tool integrates comprehensive dictionaries like Collins and Cambridge for definitions, encouraging an English-only thought process for better comprehension. With AI-powered text analysis, Write2Learn breaks down complex sentence structures, grammar, and tenses, making them easier to understand. It also provides visual sentence diagrams to clarify parts of speech and grammatical structures. Users can practice with authoritative dictionary examples and website sentences, look up words on any webpage, create fill-in-the-blank exercises, and chat with AI for immediate assistance. The platform tracks learning progress, allows customization of AI models, and offers data import/export options for convenience.

Prompt Hacker is an AI briefing service designed for executives, founders, and decision-makers building with AI. It provides weekly strategic intelligence, practical automation playbooks, and thoroughly vetted prompt frameworks. The service filters over 200 AI news sources to deliver the five most critical developments for business operations, ensuring users spend only 15 minutes reading to gain hours of competitive advantage. It includes step-by-step workflow templates, tested prompt systems for various business functions, and reviews of new AI tools with ROI estimates. Prompt Hacker also offers competitive intelligence, detailing how industry peers are deploying AI, complete with case studies and implementation timelines.

ACCAly is an AI-powered study tool designed to help students pass their ACCA exams more efficiently. It offers a comprehensive suite of features including AI tutoring for personalized guidance, exam-style practice questions with intelligent grading to simulate real test conditions, and flashcards for effective memorization. The platform also provides personalized study plans to optimize learning paths and summaries to condense complex topics. ACCAly supports all ACCA papers, making it a versatile resource for students at various stages of their qualification journey. The tool aims to accelerate exam preparation and improve pass rates through its AI-driven approach.

ExamHUB is an award-winning, globally available online examination platform designed to make learning engaging and effective for students from Grade 6 to 13. Aligned with Edexcel and Cambridge syllabuses, it offers a vast question bank of over 150,000 exam questions. The platform incorporates interactive quizzes, leaderboards, and AI-driven learning tools to revolutionize exam preparation through gamified experiences. Students can download the app, access questions, track progress, and utilize AI insights to master their subjects. Educators can also leverage ExamHUB to create engaging learning environments.

AskYourPDF is an AI-powered platform designed to help users interact with, summarize, and manage their PDF documents efficiently. Users can upload PDF files and engage with an intelligent chat AI to ask questions and extract valuable insights. The tool supports chatting with multiple documents simultaneously through its Knowledge Base feature and can generate clear, concise summaries from lengthy texts. It also offers document organization features, a Chrome extension for in-browser interaction, and integrations with Zotero and ChatGPT. AskYourPDF is GDPR compliant, ensuring data security and privacy, and is available via web, mobile app, and browser extension.

QuizMixer is an AI-powered study tool designed to convert raw notes and existing question banks into dynamic, interactive quizzes. Leveraging Gemini AI, it intelligently randomizes questions to provide a fresh learning experience every time. This platform is ideal for students and teachers looking to enhance their study routines and assessment methods. By automating the quiz generation process, QuizMixer saves valuable time, allowing users to focus more on learning and teaching. Its ability to create personalized and engaging quizzes makes it a valuable asset for anyone seeking to improve knowledge retention and make studying more efficient.

Computer-vision-in-action is a comprehensive, open-source learning platform designed for individuals interested in mastering computer vision. It offers a closed-loop learning environment where users can interactively run code directly online, eliminating the need for complex local setup. The platform features an electronic book, available in both Chinese and English, covering fundamental theories, practical applications, and advanced topics like Transformer models and generative adversarial networks. It includes detailed project guidance, code implementations, and a community forum for reader interaction and support. The platform emphasizes a 'learn by doing' approach, allowing users to modify code and observe results in real-time.

awesome-AI-books is a comprehensive GitHub repository dedicated to providing a curated list of AI-related books and PDFs. It serves as an invaluable resource for students and researchers looking to learn and download materials on artificial intelligence. The repository covers a wide range of topics, including introductory AI theory, mathematics for AI, data mining, machine learning, deep learning, philosophy of AI, quantum AI, and various AI frameworks and libraries. It also features a 'Training ground' section with links to platforms for AI experimentation and research, such as OpenAI Gym and DeepMind Pysc2. All books and PDFs are stored on Yandex.Disk due to GitHub's large file storage limitations, and the repository is intended for learning purposes only.

all-in-rag is an open-source educational resource designed for developers interested in Retrieval-Augmented Generation (RAG) technology. It offers a full-stack guide, covering RAG core concepts, data processing workflows, index building and optimization, advanced retrieval techniques, and system evaluation. The resource emphasizes hands-on practice with rich project examples, including multi-modal RAG support for text and image retrieval. It aims to provide a systematic learning path for building production-ready intelligent Q&A and knowledge retrieval systems, addressing the fragmented nature of existing RAG tutorials. The project is suitable for developers with Python programming skills and an interest in AI engineering.

AlphaTree-graphic-deep-neural-network is an open-source project offering a comprehensive AI roadmap for machine learning, deep learning, GANs, GNNs, NLP, and big data. It aims to guide users from novices to qualified engineers by providing a structured learning path, abundant source code in Python and PyTorch, and detailed explanations of fundamental concepts. The resource includes deep learning papers with official TensorFlow and Caffe source code, along with applications in recommendation algorithms and knowledge graphs. It's designed to help individuals quickly grasp cutting-edge techniques, prepare for interviews, and understand the practical application of AI in various engineering projects.

The Artificial-Intelligence-Terminology-Database is a comprehensive, open-source mapping database of English to Chinese technical vocabulary in the artificial intelligence domain. Developed by Jiqizhixin, it aims to assist researchers, translators, and students in accurately understanding and translating AI terminology. The database currently contains over 2400 professional terms, with specialized sections for Machine Learning and AI for Science. It provides indexed terms with English and Chinese translations, common abbreviations, and sources/expansions for conceptual understanding. The project emphasizes accuracy, drawing from authoritative textbooks and literature, and encourages community contributions to continuously improve and expand the terminology.

deep-learning-keras-tf-tutorial is an open-source project offering a comprehensive tutorial series for learning deep learning. It focuses on practical implementation using TensorFlow 2.0, Keras, and Python, making it suitable for beginners. The series covers a wide range of topics from fundamental concepts like activation functions and gradient descent to more advanced areas such as CNNs, transfer learning, word embeddings, and distributed training. Each topic is accompanied by code examples, allowing users to learn deep learning from scratch and build a solid foundation in the field.

DeepLearningTutorial offers a comprehensive deep learning tutorial translated into Chinese from the DeepLearning 0.1 documentation. This resource is designed for individuals looking to understand and implement deep learning algorithms and models. All examples within the tutorial are coded using Python and Theano, a powerful third-party library that enables the use of GPUs or CPUs for running Python code. The tutorial covers various topics, including getting started with deep learning, classifying MNIST digits using logistic regression, multilayer perceptrons, convolutional neural networks (LeNet), denoising autoencoders, stacked denoising autoencoders, and restricted Boltzmann machines. It serves as an excellent educational resource for Chinese-speaking students and researchers interested in the field of deep learning.