Best AI tools for< Practice Improv >

Skillora is an AI Interviewer Tool designed to help individuals practice and improve their interview skills in a safe and realistic environment. Users can take personalized mock interviews with the AI interviewer, receive instant feedback, and access learning resources to enhance their performance. Skillora offers customizable mock interviews tailored to any job description, dynamic follow-up questions, and clear scoring for each response. The application aims to boost users' confidence and success in landing their dream jobs.

AI Mock Interview is an AI-powered platform designed to help users practice and improve their interview skills. It offers realistic interview scenarios with advanced AI technology, providing instant personalized feedback and comprehensive reports to enhance performance. Users can benefit from the service by gaining confidence and improving their answers through the feedback received. The platform aims to assist individuals in preparing for real interviews by simulating the experience in a virtual environment.

Rizz AI is an AI-powered platform designed to help individuals practice and improve their social skills. The platform offers users the opportunity to practice conversations, receive feedback, and build confidence in various social scenarios. By simulating real-world interactions, Rizz AI aims to enhance users' communication skills and boost their self-assurance. With a focus on speech training and goal achievement, the platform provides personalized feedback and tailored insights to help users track their progress and identify areas for improvement.

Date Talk is an innovative and powerful AI-powered WhatsApp chatbot designed to enhance dating practice. It revolutionizes the way people connect and interact through AI technology, providing a seamless and enjoyable communication experience. Users can chat with their online matches, receive personalized feedback, and engage in meaningful conversations to improve their dating skills.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

Mursion is an immersive learning platform that utilizes human-powered AI to provide training simulations for developing interpersonal skills in various workplace scenarios. The platform offers 1:1 immersive training sessions with virtual avatars, designed to enhance communication and people skills. Mursion's simulations are supported by a team of Simulation Specialists who deliver realistic interactions to help learners practice and improve their skills effectively. The platform is backed by over a decade of research and psychology, focusing on providing a safe and impactful learning environment for individuals across different industries.

Interviews Chat is an AI-powered interview preparation tool that offers real-time suggestions, personalized question preparation, and in-depth feedback to help users ace their interviews. The tool includes a Copilot feature with vision capability for coding challenges and whiteboard tasks. Users can practice answering questions via a video interface, receive tailored interview questions based on their resume and job description, and get instant feedback on their responses. Interviews Chat aims to provide a realistic practice environment to improve interview performance and make a lasting impression.

FALTAH is an AI-powered Interview Simulation tool designed to help users practice interview questions, enhance their skills, and receive tips for their next interview. The tool utilizes artificial intelligence to provide personalized feedback, performance reports, personality analysis, and CV parsing. It aims to assist students, job seekers, and remote workers in improving their interview skills and increasing their job prospects.

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.

Readyy is an AI-powered tool designed to help users improve their reading speed and comprehension. It offers free tools and a user-friendly dashboard to track progress. The tool leverages GPT artificial intelligence to ensure fresh tests and provides a global leaderboard for competitive practice. Readyy is beneficial for individuals of all ages, from early childhood development to adult literacy and cognitive aging, by enhancing cognitive growth, vocabulary acquisition, and critical thinking skills.

ELSA is an AI-powered English speaking coach that helps you improve your pronunciation, fluency, and confidence. With ELSA, you can practice speaking English in short, fun dialogues and get instant feedback from our proprietary artificial intelligence technology. ELSA also offers a variety of other features, such as personalized lesson plans, progress tracking, and games to help you stay motivated.

ReadTheory is a free online reading comprehension practice tool for students and teachers. It offers personalized reading comprehension exercises for grades K-12 and ESL students, with adaptive technology that adjusts to each student's specific reading level. ReadTheory also provides teachers with easy-to-use reporting and thousands of interactive exercises and worksheets. With ReadTheory, teachers can save time with automatic marking, track individual student and class progress in real-time, and motivate students to read with engaging class competitions, badges, and prizes.

APEUni is an AI-powered platform designed to help users practice for the Pearson Test of English (PTE) exam. It offers various AI scoring features for different sections of the PTE exam, such as Speaking, Writing, Reading, and Listening. Users can access practice materials, study guides, and receive detailed score reports to improve their performance. APEUni aims to provide a comprehensive and efficient way for PTE test takers to prepare for the exam.

Teacher AI is a language practice tool that provides personalized speaking practice without the anxiety of interacting with a real person. It is available 24/7 for a fraction of the cost of a human teacher. Teacher AI corrects mistakes, explains grammar, and gets to know the user's learning style. It also tracks progress and provides motivation. Teacher AI is not suitable for complete beginners looking for structured lessons.

CasperPractice is an AI-powered toolkit designed to help individuals prepare for the Casper test, an open-response situational judgment test used for admissions to various professional schools. The platform offers personalized practice scenarios, instant quartile grading, detailed feedback, video answers, and a fully simulated test environment. With a large question bank and unlimited practice options, users can improve their test-taking skills and aim for a top quartile score. CasperPractice is known for its affordability, instant feedback, and realistic simulation, making it a valuable resource for anyone preparing for the Casper test.

Kippy is an AI language tutor application that allows users to practice speaking in various languages anytime, anywhere. It offers real-life conversations, pronunciation improvement, progress tracking, unlimited conversations powered by ChatGPT, natural human-like voices, instant 2-way translation, personal phrasebooks, and more. Users can engage in role-playing scenarios, test their pronunciation, track their vocabulary growth, and set daily speaking goals. The app supports English, Spanish, German, Italian, French, Korean, Japanese, Chinese, and Russian languages.

Tutor AI is an AI English-speaking application designed to assist individuals in practicing their spoken English skills with the aid of an artificial intelligence chatbot. The app offers a safe and judgment-free environment for users to engage in free-flowing, natural conversations with diverse AI characters. It provides real-time feedback, suggests better ways to express oneself, and offers adjustable features to enhance the learning experience. Tutor AI aims to improve users' spoken English skills confidently and effectively through personalized lessons and interactive learning.

Consultan is an AI tool designed to help users practice consulting interviews. It provides instant expert feedback on responses, offering unbiased reviews and suggestions. The tool is free to use and includes interview questions from top consulting firms like McKinsey, Bain, BCG, and Deloitte.

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, and solution analysis to improve coding skills and knowledge. The platform aims to provide a positive and constructive learning environment to prepare users for coding interviews with confidence.

Eloquence is an AI-powered language learning platform that offers interactive conversation practice with AI characters to help users improve their speaking skills and confidence in real-world conversations. The platform focuses on providing a safe space for users to practice without judgment, using interactive stories and native audio pronunciation to enhance the learning experience.

Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

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.

This book aims to provide readers with a comprehensive understanding of large language model technology, including its basic principles, key technologies, and application prospects. Through in-depth research and practice, we can continuously explore and improve large language model technology, and contribute to the development of the field of artificial intelligence.

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.

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.

The LLM Prompt Tuning Playbook is a comprehensive guide for improving the performance of post-trained Language Models (LLMs) through effective prompting strategies. It covers topics such as pre-training vs. post-training, considerations for prompting, a rudimentary style guide for prompts, and a procedure for iterating on new system instructions. The playbook emphasizes the importance of clear, concise, and explicit instructions to guide LLMs in generating desired outputs. It also highlights the iterative nature of prompt development and the need for systematic evaluation of model responses.

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.

This repository contains a library for constraining LLM generation to structured output, enforcing a JSON schema for precise data types and property names. It includes an acceptor/state machine framework, JSON acceptor, and JSON schema acceptor for guiding decoding in LLMs. The library provides reference implementations using Apple's MLX library and examples for function calling tasks. The tool aims to improve LLM output quality by ensuring adherence to a schema, reducing unnecessary output, and enhancing performance through pre-emptive decoding. Evaluations show performance benchmarks and comparisons with and without schema constraints.

This repository provides a comprehensive collection of AI tools and resources to enhance literature reviews. It includes a curated list of AI tools for various tasks, such as identifying research gaps, discovering relevant papers, visualizing paper content, and summarizing text. Additionally, the repository offers materials on generative AI, effective prompts, copywriting, image creation, and showcases of AI capabilities. By leveraging these tools and resources, researchers can streamline their literature review process, gain deeper insights from scholarly literature, and improve the quality of their research outputs.

This repository provides the official implementation of the paper 'On Embeddings for Numerical Features in Tabular Deep Learning'. It focuses on transforming scalar continuous features into vectors before integrating them into the main backbone of tabular neural networks, showcasing improved performance. The embeddings for continuous features are shown to enhance the performance of tabular DL models and are applicable to various conventional backbones, offering efficiency comparable to Transformer-based models. The repository includes Python packages for practical usage, exploration of metrics and hyperparameters, and reproducing reported results for different algorithms and datasets.

LLMLanding is a repository focused on practical implementation of large models, covering topics from theory to practice. It provides a structured learning path for training large models, including specific tasks like training 1B-scale models, exploring SFT, and working on specialized tasks such as code generation, NLP tasks, and domain-specific fine-tuning. The repository emphasizes a dual learning approach: quickly applying existing tools for immediate output benefits and delving into foundational concepts for long-term understanding. It offers detailed resources and pathways for in-depth learning based on individual preferences and goals, combining theory with practical application to avoid overwhelm and ensure sustained learning progress.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

OpenedAI Speech is a free, private text-to-speech server compatible with the OpenAI audio/speech API. It offers custom voice cloning and supports various models like tts-1 and tts-1-hd. Users can map their own piper voices and create custom cloned voices. The server provides multilingual support with XTTS voices and allows fixing incorrect sounds with regex. Recent changes include bug fixes, improved error handling, and updates for multilingual support. Installation can be done via Docker or manual setup, with usage instructions provided. Custom voices can be created using Piper or Coqui XTTS v2, with guidelines for preparing audio files. The tool is suitable for tasks like generating speech from text, creating custom voices, and multilingual text-to-speech applications.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

A Python package that helps Data and Analytics engineers render dbt projects in Apache Airflow DAGs. It enables teams to automatically render their dbt projects in a granular level, creating individual Airflow tasks for every model, seed, snapshot, and test within the dbt project. This allows for full control at the task-level, improving visibility and management of data models within the team.

Sports-betting is a Python library for implementing betting strategies and analyzing sports data. It provides tools for collecting, processing, and visualizing sports data to make informed betting decisions. The library includes modules for scraping data from sports websites, calculating odds, simulating betting strategies, and evaluating performance. With sports-betting, users can automate betting processes, test different strategies, and improve their betting outcomes.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

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.

Eval-Scope is a framework designed to support the evaluation of large language models (LLMs) by providing pre-configured benchmark datasets, common evaluation metrics, model integration, automatic evaluation for objective questions, complex task evaluation using expert models, reports generation, visualization tools, and model inference performance evaluation. It is lightweight, easy to customize, supports new dataset integration, model hosting on ModelScope, deployment of locally hosted models, and rich evaluation metrics. Eval-Scope also supports various evaluation modes like single mode, pairwise-baseline mode, and pairwise (all) mode, making it suitable for assessing and improving LLMs.

Your go-to partner for a great 2 person scene.

Let's get weird with a two-person improv scene

This GPT will create a practice plan with a given time based on Gold Medal Squared methodology

A guide for practicing CE5 contact protocol with a calm and respectful approach.

A versatile guide for yoga students and teachers.

Provides comprehensive guidance on educational standards and assessments.

Generates conversation examples and chunks for specified situations. Improve your instantaneous conversational skills through repetitive practice!

Get into FAANG. Practice with an AI expert in algorithms, data structures, and system design. Do a mock interview and improve.

4.5 ★ A mock interview is a practice interview, that could be useful while you're looking for a job. This GPT works for any job and any language.

Your friendly English practice partner.

Interview with Ami. An AI moderated practice interviewer created by @SprinterviewAi

Crack open the door to your future. (Partner tip: use the iPhone app for voice chat)

Learn Linux by Hands-on Labs and AI

I create detailed random UI design practice prompts.

Expert in orthopaedic practice management and strategy

Helps improve language skills through interactive scenarios and feedback.

実践スキル向上のための対話型学習アシスタント　　　　　　　　　（Interactive learning assistant to improve practical skills）

I assist with active listening practice.

Practice speaking another language like a local without being a local (use ChatGPT Voice via mobile app!)

I'm your English speaking practice buddy!