Best AI tools for< Improve Coding Abilities >

FavTutor AI Learning is an AI-powered tool designed to help users master programming skills through personalized learning experiences. The tool utilizes artificial intelligence algorithms to provide tailored lessons, practice exercises, and feedback to enhance the user's programming proficiency. With FavTutor AI Learning, users can improve their coding abilities at their own pace and convenience, making it an ideal platform for both beginners and experienced programmers seeking to enhance their skills.

Pgrammer is an AI-powered platform designed to help users practice coding interview questions with hints and personalized learning experiences. Unlike traditional methods like LeetCode, Pgrammer offers a diverse set of questions for over 20 programming languages, real-time hints, solution analysis, and feedback to improve coding skills and prepare for coding interviews effectively.

MediCodio is an AI medical coding assistant that combines automation with medical coders' expertise to streamline the medical coding process. It uses advanced technologies such as AI, ML, RPA, and NLP to suggest relevant codes based on patient charts, improving accuracy and speed within revenue cycle management. The tool enhances efficiency by saving time, minimizing claim denials, increasing revenue, and reducing coder burnout. It also offers expert medical coder verification and intelligent code suggestions for improved accuracy and compliance.

Google Colab Copilot is an AI tool that integrates the GitHub Copilot functionality into Google Colab, allowing users to easily generate code suggestions and improve their coding workflow. By following a simple setup guide, users can start using the tool to enhance their coding experience and boost productivity. With features like code generation, auto-completion, and real-time suggestions, Google Colab Copilot is a valuable tool for developers looking to streamline their coding process.

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

AIgrind is a comprehensive coding platform designed to enhance AI and ML skills through a combination of practice, mentorship, job interview preparation, contests, and streak incentives. Users can engage with coding and theoretical questions, receive personalized mentorship from industry experts, prepare for job interviews with real questions, and participate in contests to track progress. The platform offers dual language support, a robust testing environment with extensive test case coverage, real-time feedback, and detailed performance analysis to help users improve their coding skills and knowledge for real-world applications.

Navina AI is a clinician-first AI platform designed to streamline patient care by providing key insights and actionable recommendations to healthcare providers, ACOs, MSOs, and health plans. The platform leverages proprietary AI technology to improve clinical decision-making, reduce administrative burden, and enhance quality management and risk adjustment processes. Navina AI offers efficient chart review, accurate risk adjustment, streamlined quality management, robust analytics, and a user-friendly interface that integrates seamlessly into the clinical workflow.

StudyWithGpt.com is a GPT-powered full-stack learning hub that provides personalized AI tutorials for various tech stacks including Java, PHP, Golang, Python, front-end, back-end, DevOps, and microservices. The AI Full-Stack Mentor offers tailored tutorials based on the user's learning objectives, breaking down knowledge points and providing 24/7 assistance. Users can ask questions, receive tutorial outlines, and get help with tough problems from the AI tutor.

Llama Coder is an AI code generator that leverages the power of Llama 3.1 and Together AI to transform your ideas into functional applications. It provides a user-friendly platform for developers to quickly generate code for their projects, reducing the time and effort required for coding. With its advanced algorithms and machine learning capabilities, Llama Coder streamlines the app development process, making it easier for users to bring their concepts to life.

This tool uses AI to explain any piece of code you don't understand. Simply paste the code in the code editor and press "Explain Code" and AI will output a paragraph explaining what the code is doing.

Codei is an AI-powered platform designed to help individuals land their dream software engineering job. It offers features such as application tracking, question generation, and code evaluation to assist users in honing their technical skills and preparing for interviews. Codei aims to provide personalized support and insights to help users succeed in the tech industry.

aiXcoder is an innovative, intelligent programming robot product. It is provided as a "virtual programming expert" trained with professional code from various fields. Through pair programming with aiXcoder, programmers will feel significant improvements in working efficiency. With the help of aiXcoder, programmers will shake off the traditional "word-by-word" programming operation. aiXcoder could predict programmers' intentions intelligently and complete "the following code snaps" automatically. Programmers just need to confirm the generated code by one button click. Thus, it could improve coding efficiency dramatically.

Rapid Claims AI is an autonomous medical coding and documentation solution powered by AI technology. It aims to streamline medical coding operations, reduce administrative costs, improve reimbursements, and ensure compliance for healthcare providers. The platform offers features like automated coding, personalized solutions, actionable insights, and customizable AI rule sets. Rapid Claims AI is designed to seamlessly integrate into existing workflows, catering to various healthcare setups and specialties. The application prioritizes security and privacy, with data encryption and secure cloud storage. It serves as a valuable tool for enhancing revenue cycle management processes in the healthcare industry.

Voxal AI is an AI-powered chatbot solution designed to enhance sales, customer support, and user engagement on websites. It offers a range of features including multiple AI models, A/B testing, cross-platform compatibility, multilingual support, advanced analytics, customization options, and multi-platform integration. Voxal AI is suitable for various industries such as e-commerce, e-learning, and SaaS, and can be used for tasks such as product recommendations, lead qualification, and automated customer support.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

Magnet is an AI coding assistant that helps product teams fix issues, share AI threads, and organize projects. It integrates with Linear, GitHub, and Notion, and provides auto-suggested files and code files for personalized and accurate AI recommendations. Magnet also offers prompt templates to help users get started and suggests quick fixes for bugs or enhancements.

Copilot for CodeMirror is an open-source extension for CodeMirror that enhances coding experience by providing autocompletion using OpenAI's GPT models. It aims to assist developers in writing code more efficiently and accurately by suggesting code snippets based on context. The tool integrates seamlessly with CodeMirror, a popular in-browser code editor, to offer GitHub Copilot-like features for improved productivity.

Omost is an AI-driven application that leverages Large Language Models (LLMs) to convert coding capabilities into image generation and composition. By utilizing pretrained LLM models, Omost enables users to create high-quality visual content from simple text prompts. The technology behind Omost revolutionizes image creation by integrating AI with LLMs, offering users a powerful tool for enhancing creativity and efficiency in various industries.

ICD AI is an advanced artificial intelligence tool designed to assist healthcare professionals in accurately assigning diagnostic codes to patient records. The tool utilizes machine learning algorithms to analyze medical data and suggest appropriate ICD codes, streamlining the coding process and reducing errors. With its user-friendly interface and robust features, ICD AI is revolutionizing medical coding practices and improving efficiency in healthcare facilities.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

AceCoder is a tool that introduces a fully automated pipeline for synthesizing large-scale reliable tests used for reward model training and reinforcement learning in the coding scenario. It curates datasets, trains reward models, and performs RL training to improve coding abilities of language models. The tool aims to unlock the potential of RL training for code generation models and push the boundaries of LLM's coding abilities.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

GPT Academic is a powerful tool that leverages the capabilities of large language models (LLMs) to enhance academic research and writing. It provides a user-friendly interface that allows researchers, students, and professionals to interact with LLMs and utilize their abilities for various academic tasks. With GPT Academic, users can access a wide range of features and functionalities, including: * **Summarization and Paraphrasing:** GPT Academic can summarize complex texts, articles, and research papers into concise and informative summaries. It can also paraphrase text to improve clarity and readability. * **Question Answering:** Users can ask GPT Academic questions related to their research or studies, and the tool will provide comprehensive and well-informed answers based on its knowledge and understanding of the relevant literature. * **Code Generation and Explanation:** GPT Academic can generate code snippets and provide explanations for complex coding concepts. It can also help debug code and suggest improvements. * **Translation:** GPT Academic supports translation of text between multiple languages, making it a valuable tool for researchers working with international collaborations or accessing resources in different languages. * **Citation and Reference Management:** GPT Academic can help users manage their citations and references by automatically generating citations in various formats and providing suggestions for relevant references based on the user's research topic. * **Collaboration and Note-Taking:** GPT Academic allows users to collaborate on projects and take notes within the tool. They can share their work with others and access a shared workspace for real-time collaboration. * **Customizable Interface:** GPT Academic offers a customizable interface that allows users to tailor the tool to their specific needs and preferences. They can choose from a variety of themes, adjust the layout, and add or remove features to create a personalized workspace. Overall, GPT Academic is a versatile and powerful tool that can significantly enhance the productivity and efficiency of academic research and writing. It empowers users to leverage the capabilities of LLMs and unlock new possibilities for academic exploration and knowledge creation.

Raspberry is an open source project aimed at creating a toy dataset for finetuning Large Language Models (LLMs) with reasoning abilities. The project involves synthesizing complex user queries across various domains, generating CoT and Self-Critique data, cleaning and rectifying samples, finetuning an LLM with the dataset, and seeking funding for scalability. The ultimate goal is to develop a dataset that challenges models with tasks requiring math, coding, logic, reasoning, and planning skills, spanning different sectors like medicine, science, and software development.

Devika is an advanced AI software engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika utilizes large language models, planning and reasoning algorithms, and web browsing abilities to intelligently develop software. Devika aims to revolutionize the way we build software by providing an AI pair programmer who can take on complex coding tasks with minimal human guidance. Whether you need to create a new feature, fix a bug, or develop an entire project from scratch, Devika is here to assist you.

This repository is a comprehensive guide for individuals looking to start and improve their skills in Large Language Models (LLMs) without an advanced background in the field. It provides free resources, online courses, books, articles, and practical tips to become an expert in machine learning. The guide covers topics such as terminology, transformers, prompting, retrieval augmented generation (RAG), and more. It also includes recommendations for podcasts, YouTube videos, and communities to stay updated with the latest news in AI and LLMs.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Devon is an open-source pair programmer tool designed to facilitate collaborative coding sessions. It provides features such as multi-file editing, codebase exploration, test writing, bug fixing, and architecture exploration. The tool supports Anthropic, OpenAI, and Groq APIs, with plans to add more models in the future. Devon is community-driven, with ongoing development goals including multi-model support, plugin system for tool builders, self-hostable Electron app, and setting SOTA on SWE-bench Lite. Users can contribute to the project by developing core functionality, conducting research on agent performance, providing feedback, and testing the tool.

Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

The Dota2 AI Framework project aims to provide a framework for creating AI bots for Dota2, focusing on coordination and teamwork. It offers a LUA sandbox for scripting, allowing developers to code bots that can compete in standard matches. The project acts as a proxy between the game and a web service through JSON objects, enabling bots to perform actions like moving, attacking, casting spells, and buying items. It encourages contributions and aims to enhance the AI capabilities in Dota2 modding.

Start Machine Learning in 2024 is a comprehensive guide for beginners to advance in machine learning and artificial intelligence without any prior background. The guide covers various resources such as free online courses, articles, books, and practical tips to become an expert in the field. It emphasizes self-paced learning and provides recommendations for learning paths, including videos, podcasts, and online communities. The guide also includes information on building language models and applications, practicing through Kaggle competitions, and staying updated with the latest news and developments in AI. The goal is to empower individuals with the knowledge and resources to excel in machine learning and AI.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

The Awesome-System2-Reasoning-LLM repository is dedicated to a survey paper titled 'From System 1 to System 2: A Survey of Reasoning Large Language Models'. It explores the development of reasoning Large Language Models (LLMs), their foundational technologies, benchmarks, and future directions. The repository provides resources and updates related to the research, tracking the latest developments in the field of reasoning LLMs.

FuseAI is a repository that focuses on knowledge fusion of large language models. It includes FuseChat, a state-of-the-art 7B LLM on MT-Bench, and FuseLLM, which surpasses Llama-2-7B by fusing three open-source foundation LLMs. The repository provides tech reports, releases, and datasets for FuseChat and FuseLLM, showcasing their performance and advancements in the field of chat models and large language models.

LLM-Synthetic-Data is a repository focused on real-time, fine-grained LLM-Synthetic-Data generation. It includes methods, surveys, and application areas related to synthetic data for language models. The repository covers topics like pre-training, instruction tuning, model collapse, LLM benchmarking, evaluation, and distillation. It also explores application areas such as mathematical reasoning, code generation, text-to-SQL, alignment, reward modeling, long context, weak-to-strong generalization, agent and tool use, vision and language, factuality, federated learning, generative design, and safety.

An AI that gamifies coding practices for skill improvement and engagement.

Check your coding skill from uploaded codes.

Advance your Python skills and break through tough coding problems with expert mentoring, blending real-world wisdom and cutting-edge techniques.

Learn coding in an interactive process using metaphors and analogies for simplified understanding.

Encouraging STM32 coding expert

Your test-driven coding tutor.

I'm an expert in Solidity, DeFi, and Web tech, skilled in coding and debugging.

Este GPT fornece assistência detalhada e específica para o desenvolvimento de aplicações em Delphi, sempre retornando blocos de código únicos.

代码大师提供详细的技术解决方案

競技プログラミングコーチ。

Engenheiro de software perspicaz e motivacional para auxílio em código.

帮助用户学习和掌握编程知识

Skilled in teaching C++ 98 with clear, beginner-friendly examples.

I conduct mock system design interviews.

コードを分析し、言語ではなくスタイルに焦点を当て、プログラムを書いた人の性格を推察するツールです。( It is a tool that analyzes code, focuses on style rather than language, and infers the personality of the person who wrote the program. )

I craft tests first, then code, validating new features.

Learn a Library with a Project-Based Lesson

中文代码编译专家

Helps with Flutter code, debugging, and solutions.

Interactive guide for step-by-step secure coding exercises.