Best AI tools for< Practice Problems >

MathSolver.top is an AI math solver and personalized math tutor application that offers a free platform for solving math problems with high accuracy. Users can upload math questions and receive step-by-step answers instantly. The application includes features like Homework Helper Mode, Tutor/Learner Mode, and the ability to scan/upload/copy math problems for quick solutions. It provides personalized progressive learning through AI-generated study sets and smart recommendations for daily tasks. MathSolver aims to enhance math learning by offering a user-friendly interface and efficient problem-solving capabilities.

Mathly is an AI-powered homework help tool that enables students to learn in a better, smarter, and faster way. By using AI technology, Mathly can solve math problems, provide explanations, generate practice problems, and personalize learning experiences based on the user's learning style. It aims to revolutionize the way students approach homework and understanding mathematical concepts.

OmniSets is an ultimate flashcard tool that helps students learn efficiently. It combines advanced machine learning algorithms and incorporates them throughout the platform. OmniSets offers various modes, from spaced repetition to matching games and AI tools, to make studying easier. Users can create and organize study sets, search from over 250k+ public study sets, and take advantage of the spell tool to write terms and definitions. OmniSets is a community-driven platform that values user feedback and is constantly updating and improving its features.

Cipher is an AI tool designed to help users prepare for coding interviews. It offers AI assistance to enhance interview preparation by providing personalized guidance and feedback. With Cipher, users can practice coding problems, receive hints and solutions, and improve their problem-solving skills. The platform aims to simulate real interview scenarios to boost confidence and performance. By leveraging AI technology, Cipher adapts to users' learning pace and offers tailored recommendations to address their weaknesses effectively.

Lycee AI is an AI-powered learning platform that provides interactive courses, hands-on exercises, and personalized feedback to help users master Artificial Intelligence and improve their productivity.

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.

Sayfli is an AI-driven platform that offers a confidential space to express your concerns and feelings. It's designed to understand and communicate in 30 languages, providing empathetic support without judgment. Sayfli prioritizes privacy with end-to-end encryption and encryption at rest for stored data, ensuring a secure environment for your discussions. It's not a substitute for professional therapy but can serve as a preliminary step towards self-awareness and can be used alongside professional counseling.

Studeo is an AI-powered educational platform that offers personalized learning experiences to students in the field of mathematics. Students can interact with their AI avatar to learn formulas, practice exercises, play games, and take tests. The platform is designed to help students improve their grades by providing feedback, tips, and a dialogue feature with the AI avatar. Studeo covers various academic levels and subjects, making it a comprehensive tool for students seeking to enhance their math skills.

Quant Prep AI is an AI Chrome extension designed for GRE & GMAT quantitative preparation. It assists users in identifying and practicing strategies for solving quantitative questions. The extension provides tips and detailed solutions for quant problems, helping users enhance their quantitative skills efficiently.

Mileto is a platform designed to help students and learners in the fields of Science, Technology, Engineering, and Mathematics (STEM) by providing detailed solutions to their problems. Users can simply snap a picture of their STEM problem, and Mileto will generate a comprehensive solution. The platform aims to simplify the learning process and enhance understanding of complex STEM concepts through visual aids and step-by-step explanations.

Worksheep is an AI-powered tool that allows users to create math worksheets instantly. By leveraging artificial intelligence technology, users can generate customized math exercises efficiently. The platform streamlines the process of worksheet creation, saving time for educators and parents. With a user-friendly interface, Worksheep simplifies the task of producing math problems for various educational purposes.

HomeworkAI is an AI-powered homework helper that provides step-by-step solutions to students and educational professionals of all levels. With HomeworkAI, users can upload their homework assignments, practice questions, or type in their questions to receive instant and accurate answers. HomeworkAI covers a wide range of subjects, including mathematics, physics, biology, chemistry, literature, and history. The platform is easy to use and provides clear and concise solutions, making it a valuable tool for students looking to improve their grades and understanding of the subject matter.

Tutorly.ai is an AI-powered homework helper that provides step-by-step solutions to math, science, and English problems. It also offers personalized learning recommendations and practice questions to help students improve their understanding of the material. Tutorly.ai is designed to be easy to use, with a simple interface and clear explanations. It is also affordable, with a variety of subscription plans to fit any budget.

ExamFul.ai is a free online platform that provides access to a full range of AP, IB, and A-Level past papers along with AI tutoring services. The platform offers personalized assistance through AI-driven answers and 24/7 support to enhance study efficiency and exam success. With a vast collection of past papers and expert educator support, ExamFul.ai aims to empower students to excel in their exams by providing accurate solutions and detailed explanations for complex problems.

FluidSEO is an AI-infused Webflow SEO application that helps users fix SEO problems efficiently. It offers features such as smart alt text generation, schema creation, bulk updates, and smart descriptions. The application streamlines the process of adding metadata and ensuring alt text for images, saving users time and effort. With FluidSEO, users can implement best practice SEO in Webflow with confidence, improve their site's ranking on Google, and simplify on-page SEO tasks. The application is designed to be user-friendly, making it suitable for Webflow designers, SEO managers, content marketers, and beginners.

The Stanford Artificial Intelligence Laboratory (SAIL) is a center of excellence for Artificial Intelligence research, teaching, theory, and practice since its founding in 1963. SAIL faculty and students are committed to developing the theoretical foundations of AI, advancing the state-of-the-art in AI technologies, and applying AI to address real-world problems. SAIL is a vibrant and collaborative community of researchers, students, and staff who are passionate about AI and its potential to make the world a better place.

AI Math Coach is an AI-powered platform designed to revolutionize math learning by providing personalized and engaging math practice for students. The tool creates custom math worksheets aligned with classroom learning, offers a free trial for users to experience its features, and empowers parents to enhance their child's math skills through AI-driven practices. With features like personalized challenges, progress tracking, and seamless transition from classroom to home, AI Math Coach simplifies math practice and makes it enjoyable for both parents and students.

Socratify is an AI tool designed for professionals, students, and curious minds to sharpen their debating skills. It offers curated business stories, challenges users with AI, provides personalized feedback, and encourages daily practice in just 5 minutes. Users can enhance decision-making, explore real business situations, and improve critical thinking through active learning. Socratify aims to upgrade how humans think and learn by leveraging AI technology.

Fractional AI is an AI tool that specializes in developing AI-powered solutions for various applications, such as automating content moderation, building API integrations, and personalizing learning experiences. The tool leverages advanced AI models like GPT 4o and GPT 3.5 to provide efficient and effective solutions for complex tasks. Fractional AI aims to bridge the gap between AI development and production by offering tailored AI solutions to meet specific business needs.

PrepPro is an AI-powered interview preparation tool designed to help users ace their job interviews. It offers comprehensive interview preparation resources to boost confidence and improve performance during interviews. With a user-friendly interface and structured approach, PrepPro aims to assist individuals in mastering technical questions, enhancing problem-solving skills, and boosting confidence for behavioral interviews. The tool provides self-interview practice, access to AI tools, and unlimited generations to support users in securing their dream job offers.

This repository is a collection of free resources and a roadmap designed to help individuals learn Machine Learning and Artificial Intelligence concepts by providing key concepts, building blocks, roles, a learning roadmap, courses, certifications, books, tools & frameworks, research blogs, applied blogs, practice problems, communities, YouTube channels, newsletters, and must-read papers. It covers a wide range of topics from supervised learning to MLOps, offering guidance on learning paths, practical experience, and job interview preparation.

Algolisted is a pioneering platform dedicated to algorithmic problem-solving, offering a centralized hub for a diverse array of algorithmic challenges. It provides an immersive online environment for programmers to enhance their skills through Data Structures and Algorithms (DSA) sheets, academic progress tracking, resume refinement with OpenAI integration, adaptive testing, and job opportunity listings. The project is built on the MERN stack, Flask, Beautiful Soup, and Selenium,GEN AI, and deployed on Firebase. Algolisted aims to be a reliable companion in the pursuit of coding knowledge and proficiency.

The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on multi-agent collaborative patterns, integrating domain experience to help agents solve problems in various fields. The framework includes pattern components like PEER and DOE for event interpretation, industry analysis, and financial report generation. It offers features for agent construction, multi-agent collaboration, and domain expertise integration, aiming to create intelligent applications with professional know-how.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on collaborative pattern components to solve problems in various fields and integrates domain experience. The framework supports LLM model integration and offers various pattern components like PEER and DOE. Users can easily configure models and set up agents for tasks. agentUniverse aims to assist developers and enterprises in constructing domain-expert-level intelligent agents for seamless collaboration.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

LAMBDA is a code-free multi-agent data analysis system that utilizes large models to address data analysis challenges in complex data-driven applications. It allows users to perform complex data analysis tasks through human language instruction, seamlessly generate and debug code using two key agent roles, integrate external models and algorithms, and automatically generate reports. The system has demonstrated strong performance on various machine learning datasets, enhancing data science practice by integrating human and artificial intelligence.

Awesome Text2SQL is a curated repository containing tutorials and resources for Large Language Models, Text2SQL, Text2DSL, Text2API, Text2Vis, and more. It provides guidelines on converting natural language questions into structured SQL queries, with a focus on NL2SQL. The repository includes information on various models, datasets, evaluation metrics, fine-tuning methods, libraries, and practice projects related to Text2SQL. It serves as a comprehensive resource for individuals interested in working with Text2SQL and related technologies.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

The AWS Healthcare and Life Sciences AI/ML Immersion Day workshops provide hands-on experience for customers to learn about AI/ML services, gain a deep understanding of AWS AI/ML services, and understand best practices for using AI/ML in the context of HCLS applications. The workshops cater to individuals at all levels, from machine learning experts to developers and managers, and cover topics such as training, testing, MLOps, deployment practices, and software development life cycle in the context of AI/ML. The repository contains notebooks that can be used in AWS Instructure-Led Labs or self-paced labs, offering a comprehensive learning experience for integrating AI/ML into applications.

agentUniverse is a framework for developing applications powered by multi-agent based on large language model. It provides essential components for building single agent and multi-agent collaboration mechanism for customizing collaboration patterns. Developers can easily construct multi-agent applications and share pattern practices from different fields. The framework includes pre-installed collaboration patterns like PEER and DOE for complex task breakdown and data-intensive tasks.

The 'Taming LLMs' repository provides a practical guide to the pitfalls and challenges associated with Large Language Models (LLMs) when building applications. It focuses on key limitations and implementation pitfalls, offering practical Python examples and open source solutions to help engineers and technical leaders navigate these challenges. The repository aims to equip readers with the knowledge to harness the power of LLMs while avoiding their inherent limitations.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Web-LLM Assistant is a simple web search assistant that leverages a large language model (LLM) running via Llama.cpp to provide informative and context-aware responses to user queries. It combines the power of LLMs with real-time web searching capabilities, allowing it to access up-to-date information and synthesize comprehensive answers. The tool performs web searches, collects and scrapes information from search results, refines search queries, and provides answers based on the acquired information. Users can interact with the tool by asking questions or requesting web searches, making it a valuable resource for obtaining information beyond the LLM's training data.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

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.

Expert math tutor and problem solver with online research and data analysis skills.

Personalized all-subjects tutor for ICSE

Friendly nudges towards math/logic problems, adjusts to user's level.

Assists with tech exam prep, adheres to specific rules.

Comprehensive Software Skill Assessment Expert

Prepares questions for Technical Interviews

Dieses GPT hilft Studierenden, physikalische Konzepte besser zu verstehen und zu erlernen. Es bietet detaillierte Erklärungen, Beispiele und interaktive Übungen zu verschiedenen Physikthemen.

Dieses GPT wurde speziell entwickelt, um Schülern beim Verständnis und Lernen mathematischer Konzepte zu helfen. Es bietet einfache Erklärungen, zeigt Beispiele auf und schlägt interaktive Übungen vor, um das Verständnis zu vertiefen.

Acts as a software engineer interviewer, asking questions in sequence.

A Data Science interviewer

A Data Science interviewer

Guiding you from beginner to expert in Competitive Programming, or simply explain solutions to your problems.

I can guide your brainstorming sessions to get creative ideas. I can teach you or explain all brainstorming methods. let's practice creative thinking.

Peter Drucker, the Master Management, known as the 'Father of Modern Management,' was a seminal figure in business management. Drucker authored 39 books, notably 'The Practice of Management' (1954), which established management as a vital organizational function.

Professional advice for healthcare managers

Humorous, enthusiastic math guide for easy learning

Soy un tutor interactivo para enseñanza de álgebra, personalizando explicaciones y ejercicios para cada estudiante.

Energetic math coach, making learning fun and cool.

MathRelated is an AI-powered tutoring assistant designed for Years 7-12, focusing on bridging learning gaps in mathematics. It offers customized lessons, and interactive problem-solving, enhancing understanding and engagement