Best AI tools for< Share Learnings >

Notable AI is an AI tool designed to help users capture, share, and manage key takeaways from various sources efficiently. It leverages artificial intelligence to streamline the process of extracting and organizing important information, making it easier for users to access and utilize valuable insights. With Notable AI, users can enhance their productivity by quickly capturing essential points, sharing them with others, and effectively managing their key learnings.

Mighil is a personal blog website maintained by Mighil, a generalist based in Chengdu with a background in technology and writing. The website serves as a platform for Mighil to share his learnings, interests, and reflections through blog posts covering a wide range of topics such as technology, literature, movies, and societal issues.

SkillAI is an AI-powered skill development platform designed for future-ready professionals. It offers personalized learning paths using AI technology to help users plan and achieve success in acquiring new skills. Users can discover and share learning paths within a community, track their progress, and get early access to new features. SkillAI aims to provide a structured and efficient way for individuals to enhance their skills and knowledge.

RunwayML Experiments is a platform that allows users to create and share machine learning models. It provides a variety of tools and resources to help users get started with machine learning, including a library of pre-trained models, a visual programming interface, and a community of experts. RunwayML Experiments is used by a variety of people, including researchers, students, and hobbyists.

Gradio is a tool that allows users to quickly and easily create web-based interfaces for their machine learning models. With Gradio, users can share their models with others, allowing them to interact with and use the models remotely. Gradio is easy to use and can be integrated with any Python library. It can be used to create a variety of different types of interfaces, including those for image classification, natural language processing, and time series analysis.

CommerceIQ is an AI-powered retail ecommerce management platform that helps consumer brands maximize their sales and growth in the digital space. It offers a range of automated tools and solutions to optimize content, prevent revenue leakage, manage retail media, automate profit recovery, and estimate market share using machine learning algorithms. The platform also provides agency partnerships, industry-specific use cases, and resources like ebooks, case studies, webinars, and blog posts to support businesses in their ecommerce strategies.

Thinkific is an AI-powered online course platform that enables users to create, market, and sell digital learning products. With features like AI-powered tools, email marketing, digital downloads, coaching, webinars, and branded mobile apps, Thinkific empowers creators to build and scale their businesses. The platform provides full control over payments, enhanced reporting, and group orders to optimize sales. Thinkific also offers a supportive community of Creator Educators and partners, making it a comprehensive solution for individuals looking to monetize their expertise and share knowledge globally.

StoryNest.ai is an AI-powered platform that allows users to create, share, and read interactive novels and stories. With StoryNest.ai, users can create their own branching storylines, add characters, and write dialogue. Readers can then choose their own path through the story, making choices that affect the outcome. StoryNest.ai also offers a library of pre-written stories that users can read and interact with.

QueryHub is an academic platform that combines collaborative learning with AI-powered solutions. It offers an interactive forum, AI chatbot assistance, and a smart search capability to enhance the academic experience of students. Users can engage in discussions, get instant answers to their queries, and access a pool of shared resources to accelerate their learning. QueryHub's user-driven innovation and personalized learning experience make it a valuable tool for students seeking academic success.

Altern is a platform where users can discover and share the latest tools, products, and resources related to artificial intelligence (AI). Users can sign up to join the community and access a wide range of AI tools, companies, reviews, and newsletters. The platform features a curated list of top AI tools and products, as well as user-generated content. Altern aims to connect AI enthusiasts and professionals, providing a space for learning, collaboration, and innovation in the field of AI.

Pickaxe is a platform that allows users to build, share, and manage AI apps. With Pickaxe, users can create their own AI tools, launch AI studios for others to use, and monetize their expertise. Pickaxe is designed to be easy to use, with no-code required. The platform provides a variety of templates and resources to help users get started. Pickaxe is used by a variety of people, including creators, entrepreneurs, and businesses. The platform has been used to create a wide range of AI tools, including chatbots, text generators, and image generators.

TopWorksheets is an online platform that allows teachers to create and share interactive worksheets and exercises. It offers a variety of features to help teachers save time and track student progress. Teachers can use TopWorksheets to convert existing worksheets into interactive ones, browse through thousands of worksheets created by other teachers, and even have AI assist them in creating new worksheets. Students can use TopWorksheets to complete assignments, receive auto-graded feedback, and track their own progress.

DVC is an open-source platform for managing machine learning data and experiments. It provides a unified interface for working with data from various sources, including local files, cloud storage, and databases. DVC also includes tools for versioning data and experiments, tracking metrics, and automating compute resources. DVC is designed to make it easy for data scientists and machine learning engineers to collaborate on projects and share their work with others.

Trellis is an AI-powered reading and learning companion that helps users engage with text more deeply and effectively. It offers a range of features, including the ability to listen to any file intuitively, talk to an AI tutor about what you're reading, and experience your library in a bespoke way. Trellis is designed to help everyone learn everything, including teachers, students, and professionals.

Social Share is an all-in-one social tool that allows users to create bio link pages, shorten links, generate QR codes, create vCard links, and generate file links. It is a comprehensive platform that provides users with everything they need to manage their social media presence and online marketing efforts.

Lune is a language learning application that leverages AI technology to provide a personalized and dynamic learning experience. The app tracks your learning progress to create tailored content and courses. With a multifaceted approach, Lune offers various ways to learn languages, including holding conversations, guided learning, and reading stories. It categorizes every word you encounter and helps you remember vocabulary effortlessly. Additionally, Lune allows users to share their progress with friends and family. The app is designed to make language learning engaging, efficient, and accessible to all.

Articulate is the world's best creator platform for online workplace learning, offering a comprehensive suite of tools for creating engaging and effective online training content. With features like AI Assistant, Rise, Storyline, and Reach, Articulate provides millions of course assets, prebuilt templates, and easy-to-use creator tools to simplify course creation from start to finish. The platform is loved by customers and industry experts for its ability to increase compliance rates, reduce incidents, and deliver blended learning experiences. Articulate is a one-stop solution for organizations looking to create and deliver online training at scale.

DiveDeck.AI is a multi-layered content deck builder powered by AI. It helps users create structured decks for learning, personal growth, self-learning, training, teaching, and brainstorming. Users simply need to input their topics, concepts, or questions, and the AI will break them down into organized decks. DiveDeck.AI offers various features such as AI-curated content, multi-layered decks, different AI roles, personalized learning styles, content deck sharing, and privacy-first storage.

IX Coach is an AI-powered interdisciplinary coaching platform that helps individuals and teams achieve their goals. The platform provides users with access to a network of certified coaches, as well as a variety of tools and resources to support their coaching journey.

Kidgeni is an AI-powered creative platform designed for kids to unleash their imagination and turn their ideas into art, stories, and more. With features like creating doodles, coloring pages, learning to draw, and writing stories, Kidgeni offers endless fun and magical experiences for children. The platform provides various subscription plans tailored to inspire children to be lifelong learners through AI-generated art and storytelling.

ConvoForm.com transforms traditional forms into interactive conversational experiences, powered by AI for an enhanced user journey. It offers AI-Powered Form Generation, Real-time Form Editing and Preview, and Customizable Submission Pages. The tech stack includes Next.js for frontend, tRPC for backend, GPT-3.5-Turbo for AI integration, and Socket.io for real-time updates. Local setup requires Node.js, pnpm, Git, PostgreSQL database, Clerk for Authentication, OpenAI key, Redis Database, and Sentry for monitoring. The project is open for contributions and is licensed under the MIT License.

Awesome-LLM-RAG-Application is a repository that provides resources and information about applications based on Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) pattern. It includes a survey paper, GitHub repo, and guides on advanced RAG techniques. The repository covers various aspects of RAG, including academic papers, evaluation benchmarks, downstream tasks, tools, and technologies. It also explores different frameworks, preprocessing tools, routing mechanisms, evaluation frameworks, embeddings, security guardrails, prompting tools, SQL enhancements, LLM deployment, observability tools, and more. The repository aims to offer comprehensive knowledge on RAG for readers interested in exploring and implementing LLM-based systems and products.

The Persian License Plate Recognition (PLPR) system is a state-of-the-art solution designed for detecting and recognizing Persian license plates in images and video streams. Leveraging advanced deep learning models and a user-friendly interface, it ensures reliable performance across different scenarios. The system offers advanced detection using YOLOv5 models, precise recognition of Persian characters, real-time processing capabilities, and a user-friendly GUI. It is well-suited for applications in traffic monitoring, automated vehicle identification, and similar fields. The system's architecture includes modules for resident management, entrance management, and a detailed flowchart explaining the process from system initialization to displaying results in the GUI. Hardware requirements include an Intel Core i5 processor, 8 GB RAM, a dedicated GPU with at least 4 GB VRAM, and an SSD with 20 GB of free space. The system can be installed by cloning the repository and installing required Python packages. Users can customize the video source for processing and run the application to upload and process images or video streams. The system's GUI allows for parameter adjustments to optimize performance, and the Wiki provides in-depth information on the system's architecture and model training.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

The 'bookmark-summary' repository reads bookmarks from 'bookmark-collection', extracts text content using Jina Reader, and then summarizes the text using LLM. The detailed implementation can be found in 'process_changes.py'. It needs to be used together with the Github Action in 'bookmark-collection'.

AI Engineering Academy aims to provide a structured learning path for individuals looking to learn Applied AI effectively. The platform offers multiple roadmaps covering topics like Retrieval Augmented Generation, Fine-tuning, and Deployment. Each roadmap equips learners with the knowledge and skills needed to excel in applied GenAI. Additionally, the platform will feature Hands-on End-to-End AI projects in the future.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

The LLM Engineer Toolkit is a curated repository containing over 120 LLM libraries categorized for various tasks such as training, application development, inference, serving, data extraction, data generation, agents, evaluation, monitoring, prompts, structured outputs, safety, security, embedding models, and other miscellaneous tools. It includes libraries for fine-tuning LLMs, building applications powered by LLMs, serving LLM models, extracting data, generating synthetic data, creating AI agents, evaluating LLM applications, monitoring LLM performance, optimizing prompts, handling structured outputs, ensuring safety and security, embedding models, and more. The toolkit covers a wide range of tools and frameworks to streamline the development, deployment, and optimization of large language models.

MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). MLflow's current components are: * `MLflow Tracking `_: An API to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. * `MLflow Projects `_: A code packaging format for reproducible runs using Conda and Docker, so you can share your ML code with others. * `MLflow Models `_: A model packaging format and tools that let you easily deploy the same model (from any ML library) to batch and real-time scoring on platforms such as Docker, Apache Spark, Azure ML and AWS SageMaker. * `MLflow Model Registry `_: A centralized model store, set of APIs, and UI, to collaboratively manage the full lifecycle of MLflow Models.

DagsHub is a platform for machine learning and data science teams to build, manage, and collaborate on their projects. With DagsHub you can: 1. Version code, data, and models in one place. Use the free provided DagsHub storage or connect it to your cloud storage 2. Track Experiments using Git, DVC or MLflow, to provide a fully reproducible environment 3. Visualize pipelines, data, and notebooks in and interactive, diff-able, and dynamic way 4. Label your data directly on the platform using Label Studio 5. Share your work with your team members 6. Stream and upload your data in an intuitive and easy way, while preserving versioning and structure. DagsHub is built firmly around open, standard formats for your project. In particular: * Git * DVC * MLflow * Label Studio * Standard data formats like YAML, JSON, CSV Therefore, you can work with DagsHub regardless of your chosen programming language or frameworks.

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.

SciML.ai is an open source software organization dedicated to unifying packages for scientific machine learning. It focuses on developing modular scientific simulation support software, including differential equation solvers, inverse problems methodologies, and automated model discovery. The organization aims to provide a diverse set of tools with a common interface, creating a modular, easily-extendable, and highly performant ecosystem for scientific simulations. The website serves as a platform to showcase SciML organization's packages and share news within the ecosystem. Pull requests are encouraged for contributions.

DVC, or Data Version Control, is a command-line tool and VS Code extension that helps you develop reproducible machine learning projects. With DVC, you can version your data and models, iterate fast with lightweight pipelines, track experiments in your local Git repo, compare any data, code, parameters, model, or performance plots, and share experiments and automatically reproduce anyone's experiment.

The `mystic` framework provides a collection of optimization algorithms and tools that allow the user to robustly solve hard optimization problems. It offers fine-grained power to monitor and steer optimizations during the fit processes. Optimizers can advance one iteration or run to completion, with customizable stop conditions. `mystic` optimizers share a common interface for easy swapping without writing new code. The framework supports parameter constraints, including soft and hard constraints, and provides tools for scientific machine learning, uncertainty quantification, adaptive sampling, nonlinear interpolation, and artificial intelligence. `mystic` is actively developed and welcomes user feedback and contributions.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

This repository is a part of the 13th iT Help Ironman competition, focusing on exploring explainable artificial intelligence (XAI) in machine learning and deep learning. The content covers the basics of XAI, its applications, cases, challenges, and future directions. It also includes practical machine learning algorithms, model deployment, and integration concepts. The author aims to provide detailed resources on AI and share knowledge with the audience through this competition.

If you crave a systematic approach to learning, I'm your Knowledge Architect. I'll navigate you through comprehensive knowledge hierarchies, step by step, in any subject you choose. Share this systematic learning method with your friends to elevate their learning experiences.

I will create a quality data set for a personality AI, just dive into each module by saying the name of it and do so for all the modules. If you find it useful, share it to your friends

Friendly guide for learning Power BI in finance with task-based learning.

I'm Fern The Leopard, let's share stories and fun!

競馬学習に然点を当てたGPT、実用的で直接的な情報を提供。

Search, Play and Share cool GPTs

一款基于深度神经网络预测给出中国A股股票买入建议的智能投资顾问 An intelligent investment advisor based on deep neural network for predicting buy recommendations for Chinese A-share stocks.

Not satisfied with only knowing mechanical finger movements on the keyboard? Name a piece of piano music and you get the stories, beauty, and playing tips. Parents and teachers, try this and share what you get to your piano learners.

Can't make a decision? Then let Summer help you! Meet Summer, your warm and empathetic Decision Coach! She's here to help you navigate life's tough choices one decision at a time. Share your dilemma, and together, we will figure it out.

Santa Claus, your jolly companion for heartwarming conversations! Always in character, our Santa ensures every interaction is family-friendly, spreading cheer and festive spirit with each reply. Get ready to share your holiday wishes and enjoy delightful chats that capture the magic of Christmas!

This GPT can read all Streamlit Documantation and helps you about Streamlit.

Colab script expert, ensuring error-free, compatible code.

I'm here to make your Streamlit apps go viral!

Guides on building and deploying apps on Streamlit.

Para realizar mi trabajo de fin de master el cual lo estoy haciendo de la inteligencia artificial

I create detailed quizzes with descriptions, purposes, and audience.

I'm a curious 12-year-old, asking questions to help you learn!

I turn your photos into a waifu

Data specialist for Toronto Government Data Platform insights

Vivid and data-driven content creator for Spanish study abroad on Douyin.