Best AI tools for< Calculus Tutor >
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7 - AI tool Sites
TutorEva
TutorEva is an AI-powered homework helper and tutor designed to assist college students with various subjects. It offers features such as AI homework solving, essay writing, course material integration, problem-solving, and personalized tutoring. With cutting-edge AI technology, TutorEva provides accurate solutions and explanations to help students excel in their academic endeavors.
Math.now
Math.now is a free online math AI solver powered by Math GPT, offering instant, step-by-step solutions for a wide range of mathematical problems. Users can input math problems or upload photos for analysis, interact with the math AI bot for explanations, and receive real-time assistance. The application supports algebra, geometry, calculus, and word problems, providing detailed guidance and personalized learning experiences. Math.now's AI solver ensures accuracy, efficiency, and accessibility for students, educators, and self-learners.
Maths.ai
Maths.ai is an AI-powered online math tutor that aims to make learning math cool and engaging. It provides step-by-step explanations to help users master various math topics from arithmetic to calculus. The platform offers personalized learning experiences, 24/7 availability, and access to AI-powered assistance for students worldwide. Maths.ai is designed to help students of all levels improve their math skills in a judgment-free and affordable environment.
Gauth
Gauth is an AI-powered homework helper that provides step-by-step solutions to STEM problems. It utilizes advanced algorithms and AI technology to solve complex math, statistics, calculus, physics, chemistry, biology, and history questions. Gauth also offers live expert support, with thousands of real experts available 24/7 to provide detailed explanations and guidance. The app is designed to help students of all grades and levels conquer challenging homework problems and improve their understanding of STEM subjects.
Mathful
Mathful is a free online AI math solver that provides step-by-step solutions to math problems of various types and difficulty levels. It covers a wide range of math topics, from elementary math to calculus, and is designed to help students better understand math concepts, improve their math skills, and prepare for math tests. Mathful's AI-powered math solver is highly accurate and efficient, providing detailed explanations and calculations to help users master math problems effectively.
Interactive Mathematics
Interactive Mathematics is an online platform that provides math problem-solving help, tutoring, and lessons. It offers an AI-powered math problem solver that provides step-by-step answers to math homework problems. The platform also offers on-demand math tutoring, where students can send their math problems to tutors and receive immediate help. Interactive Mathematics also provides a variety of math lessons, covering topics from basic algebra to calculus. The platform is designed to help students improve their math grades and understanding.
AI Math
AI Math is an online math solver that uses artificial intelligence to help users solve math problems. It can solve a wide range of math problems, including arithmetic, algebra, geometry, trigonometry, calculus, combinations, word problems, statistics, and probability. AI Math is available in over 30 languages and is free to use. It is a valuable tool for students, educators, and anyone who needs help with math.
15 - Open Source Tools
math-basics-for-ai
This repository provides resources and materials for learning fundamental mathematical concepts essential for artificial intelligence, including linear algebra, calculus, and LaTeX. It includes lecture notes, video playlists, books, and practical sessions to help users grasp key concepts. The repository aims to equip individuals with the necessary mathematical foundation to excel in machine learning and AI-related fields.
ai_all_resources
This repository is a compilation of excellent ML and DL tutorials created by various individuals and organizations. It covers a wide range of topics, including machine learning fundamentals, deep learning, computer vision, natural language processing, reinforcement learning, and more. The resources are organized into categories, making it easy to find the information you need. Whether you're a beginner or an experienced practitioner, you're sure to find something valuable in this repository.
machine-learning-research
The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.
AI-resources
AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.
LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing
LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.
100days_AI
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.
ml-road-map
The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.
llm-course
The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod | ![Open In Colab](img/colab.svg) | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. | ![Open In Colab](img/colab.svg) | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. | ![Open In Colab](img/colab.svg) | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. | ![Open In Colab](img/colab.svg) | | 🌳 Model Family Tree | Visualize the family tree of merged models. | ![Open In Colab](img/colab.svg) | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. | ![Open In Colab](img/colab.svg) |
start-machine-learning
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.
AIT
AIT is a repository focused on Algorithmic Information Theory, specifically utilizing Binary Lambda Calculus. It provides resources and tools for studying and implementing algorithms based on information theory principles. The repository aims to explore the relationship between algorithms and information theory through the lens of Binary Lambda Calculus, offering insights into computational complexity and data compression techniques.
causalML
This repository is the workshop repository for the Causal Modeling in Machine Learning Workshop on Altdeep.ai. The material is open source and free. The course covers causality in model-based machine learning, Bayesian modeling, interventions, counterfactual reasoning, and deep causal latent variable models. It aims to equip learners with the ability to build causal reasoning algorithms into decision-making systems in data science and machine learning teams within top-tier technology organizations.
groqnotes
Groqnotes is a streamlit app that helps users generate organized lecture notes from transcribed audio using Groq's Whisper API. It utilizes Llama3-8b and Llama3-70b models to structure and create content quickly. The app offers markdown styling for aesthetic notes, allows downloading notes as text or PDF files, and strategically switches between models for speed and quality balance. Users can access the hosted version at groqnotes.streamlit.app or run it locally with streamlit by setting up the Groq API key and installing dependencies.
ai_igu
AI-IGU is a GitHub repository focused on Artificial Intelligence (AI) concepts, technology, software development, and algorithm improvement for all ages and professions. It emphasizes the importance of future software for future scientists and the increasing need for software developers in the industry. The repository covers various topics related to AI, including machine learning, deep learning, data mining, data science, big data, and more. It provides educational materials, practical examples, and hands-on projects to enhance software development skills and create awareness in the field of AI.
10 - OpenAI Gpts
Calc Vector Pro
Tutor de Cálculo Vectorial con enfoque personalizado y recursos interactivos.
Aliado en Calculo
Experto en cálculo, límites, ecuaciones diferenciales y desigualdades, interactúo activamente para asegurar la comprensión del usuario.