Best AI tools for< Visualize Progress >

FAT2FIT is an AI-powered application that helps users visualize their body transformation goals. By utilizing advanced AI technology, the platform generates personalized body transformation photos to assist individuals in reaching their fitness objectives. With over 6,587 AI body transformation photos already created, users can see their future selves and work towards becoming the best version of themselves. FAT2FIT offers a unique opportunity to visualize and track progress through AI-assisted before and after photos, providing motivation and inspiration for achieving fitness goals.

This Beach Does Not Exist is an AI application powered by StyleGAN2-ADA network, capable of generating realistic beach images. The website showcases AI-generated beach landscapes created from a dataset of approximately 20,000 images. Users can explore the training progress of the network, generate random images, utilize K-Means Clustering for image grouping, and download the network for experimentation or retraining purposes. Detailed technical information about the network architecture, dataset, training steps, and metrics is provided. The application is based on the GAN architecture developed by NVIDIA Labs and offers a unique experience of creating virtual beach scenes through AI technology.

Fit AI is a visual application that allows users to visualize their dream body using Generative AI technology. By simply uploading a selfie, users can get inspired to stay on their fitness journey. The application is 100% free and powered by Replicate, Upload, and Vercel.

Codlixe is an AI-powered application designed to help users balance their life goals and journal effectively. With the assistance of AI, users can set goals that bring balance to various areas of their lives and receive journaling prompts to kickstart their writing journey. The application tracks and categorizes goals, provides suggestions for goal setting based on progress analysis, and offers journaling prompts to inspire users. Codlixe aims to be a growth companion for users, guiding them towards a more balanced and fulfilling life.

Lychee is an all-in-one data platform designed to streamline the data workflow process, from data collection to analysis, visualization, and sharing. It offers powerful features such as instant graph generation, AI data analysis, website deployment, social media sharing, and team collaboration. Lychee aims to simplify complex data tasks and help users make faster progress in their data-related projects.

Ogoodo is a Kanban tool that helps teams to visualize their workflow, track their progress, and improve their productivity. It offers a variety of features to support the Kanban framework, including a board view, time tracking, timeline prediction, and analytics. Ogoodo is designed to be easy to use and can be customized to fit the needs of any team.

Visionboards AI is an AI-powered platform that helps users visualize and achieve their goals by creating personalized vision boards. The platform uses AI to generate inspiring images aligned with users' aspirations, fueling confidence and motivation. Users can share their goals, generate customized vision boards, and stay motivated to turn their dreams into reality. Visionboards AI offers different pricing packages with unique features and benefits, including high-resolution visuals, psychology-backed success visualization, and commercial use licenses. The platform aims to empower users to see themselves achieving their specific goals and progress through stages of their journey.

Wizdom.ai is an AI-powered research intelligence platform that provides comprehensive insights into the global research ecosystem. It continuously monitors billions of data points to generate analytics about scientific developments, helping users make informed decisions and progress research further and faster. Wizdom.ai offers a range of features, including:

Extrapolate is an AI-powered tool that allows users to transform their faces using Artificial Intelligence technology. Users can see how they will age in the future by uploading a photo and getting a glimpse of their appearance in 10, 20, or even 90 years. With over 377.1K photos generated and counting, Extrapolate provides a fun and engaging way to visualize the aging process through the lens of AI.

Cloudinary is a cloud-based platform that provides image and video management, optimization, and delivery services. It offers a range of features including image and video storage, transformation, optimization, and delivery, as well as AI-powered features such as generative AI, machine learning, and content-aware AI. Cloudinary's platform is designed to help businesses improve the performance, engagement, and efficiency of their visual content.

Uizard is an AI-powered UI design tool that simplifies the process of creating user interfaces, wireframes, mockups, and prototypes. It offers a range of features that enable users to generate designs quickly and easily using AI technology. With Uizard, users can visualize and iterate on their design ideas in minutes, empowering product teams to bring their concepts to life effortlessly.

BabyFaceGenerator is an AI-based tool that analyzes up to 70 facial features of two partners to generate the face of a future baby. While it provides entertainment by predicting what a baby might look like, it is important to note that genetics are much more complex than the tool can accurately represent. The tool is available in multiple languages and offers a fun way for users to visualize potential offspring.

Spacely AI is an AI rendering solution that specializes in interior, room, and home design. It utilizes advanced artificial intelligence algorithms to create realistic and immersive visualizations of interior spaces. With Spacely AI, users can easily experiment with different design elements, layouts, and color schemes to bring their ideas to life. Whether you are an interior designer, architect, or homeowner, Spacely AI provides a powerful tool to visualize and plan your design projects with precision and creativity.

Code to Flowchart is an AI-powered tool that helps users visualize and understand program logic instantly. It allows users to convert code into interactive flowcharts with the help of AI analysis. The tool supports all major programming languages, identifies code paths and logic flows, and offers multiple visualization options like flowcharts, sequence diagrams, and class diagrams. Users can export diagrams in various formats and customize color schemes and themes. Code to Flowchart aims to simplify complex code structures and enhance collaboration among developers.

SeeYourBabyAI is an AI-powered platform that offers a unique service to predict the appearance of your future baby based on photos of you and your partner. By leveraging advanced AI technology, the platform generates realistic images of potential sons and daughters with a high level of accuracy. Users can upload their photos, receive multiple AI-generated baby photos, and share them with family and friends. The platform focuses on precision, respects ethnic backgrounds, ensures privacy through encryption, and provides high-resolution, realistic photos for a one-time payment. SeeYourBabyAI aims to provide users with a heartwarming and fun experience of visualizing their future children.

Getfloorplan is an AI-powered platform that allows users to create 2D and 3D floor plans, as well as virtual tours for real estate properties. The application offers various sets of property visuals at different price points, starting from basic 2D plans to high-quality renderings. Users can upload a floor plan and receive realistic and attractive visuals within 24 hours, without the need for human involvement. Getfloorplan guarantees the lowest price and offers a money-back guarantee if users are unsatisfied with the results.

VisualizeAI is a powerful AI-powered platform that helps businesses visualize and analyze their data. With VisualizeAI, you can easily create stunning data visualizations, dashboards, and reports that will help you make better decisions. VisualizeAI is perfect for businesses of all sizes, from startups to large enterprises. It is easy to use and affordable, and it can help you save time and money while improving your decision-making.

Tilesview is a cutting-edge 3D room visualizer and tile visualizer application powered by advanced AI technology. It allows users to visualize walls, floors, rugs, paint colors, tiles, wallpapers, and carpets in a virtual space with precision. The tool revolutionizes the way businesses in the flooring and wall covering industry operate, enabling faster decision-making, increased customer engagement, and higher conversion rates. With features like core products visualizer, 360 panorama view, generating catalogs, and website integration, Tilesview offers a comprehensive solution for manufacturers, distributors, retailers, and e-commerce platforms. The application caters to various roles such as importers/exporters, tiles designers, digital media marketers, and sales professionals, empowering them with tools to enhance visualization, marketing efforts, and sales conversions.

Quick Dreamviz is an instant dream home visualization tool that allows users to redesign their rooms using AI technology. With just a few clicks, users can upload a photo of their room, select a room type and theme, and watch as the AI generates a new design. Quick Dreamviz is perfect for anyone who wants to see how their dream home will look before it becomes a reality.

Bristles AI is a powerful AI tool designed for DIY enthusiasts, furniture designers, and home renovators. It allows users to create design mock-ups for furniture flips and home updates, helping them visualize and customize their projects before diving into the actual work. With features like generating design ideas, customizing designs, and sharing clear mock-ups, Bristles AI empowers users to bring their creative visions to life with confidence. The application has garnered praise from furniture artists, contractors, and DIYers for its user-friendly interface and ability to streamline the design process.

Substrate is an open-source framework designed for human understanding, meaning, and progress. It provides a platform for individuals to contribute by modifying various object files such as Problems, Solutions, and Ideas. The project aims to visualize human progress and offers a web-based interface to facilitate non-coders in contributing. Substrate was created by Daniel Miessler in July 2024 and has a single-repo structure for easier project management. The tool emphasizes collaboration and inspiration from contributors like Jonathan Dunn, Joel Parish, and Joseph Thacker.

PyTorch Lightning is a framework for training and deploying AI models. It provides a high-level API that abstracts away the low-level details of PyTorch, making it easier to write and maintain complex models. Lightning also includes a number of features that make it easy to train and deploy models on multiple GPUs or TPUs, and to track and visualize training progress. PyTorch Lightning is used by a wide range of organizations, including Google, Facebook, and Microsoft. It is also used by researchers at top universities around the world. Here are some of the benefits of using PyTorch Lightning: * **Increased productivity:** Lightning's high-level API makes it easy to write and maintain complex models. This can save you time and effort, and allow you to focus on the research or business problem you're trying to solve. * **Improved performance:** Lightning's optimized training loops and data loading pipelines can help you train models faster and with better performance. * **Easier deployment:** Lightning makes it easy to deploy models to a variety of platforms, including the cloud, on-premises servers, and mobile devices. * **Better reproducibility:** Lightning's logging and visualization tools make it easy to track and reproduce training results.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

RAGEN is a reinforcement learning framework designed to train reasoning-capable large language model (LLM) agents in interactive, stochastic environments. It addresses challenges such as multi-turn interactions and stochastic environments through a Markov Decision Process (MDP) formulation, Reason-Interaction Chain Optimization (RICO) algorithm, and progressive reward normalization strategies. The framework enables LLMs to reason and interact with the environment, optimizing entire trajectories for long-horizon reasoning while maintaining computational efficiency.

MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.

RAGEN is a reinforcement learning framework designed to train reasoning-capable large language model (LLM) agents in interactive, stochastic environments. It addresses challenges such as multi-turn interactions and stochastic environments through a Markov Decision Process (MDP) formulation, Reason-Interaction Chain Optimization (RICO) algorithm, and progressive reward normalization strategies. The framework consists of MDP formulation, RICO algorithm with rollout and update stages, and reward normalization strategies to stabilize training. RAGEN aims to optimize reasoning and action strategies for LLM agents operating in complex environments.

This repository evaluates Large Language Models (LLMs) trained on PGN format chess games using linear probes. It assesses the LLMs' internal understanding of board state and their ability to estimate player skill levels. The repo provides tools to train, evaluate, and visualize linear probes on LLMs trained to play chess with PGN strings. Users can visualize the model's predictions, perform interventions on the model's internal board state, and analyze board state and player skill level accuracy across different LLMs. The experiments in the repo can be conducted with less than 1 GB of VRAM, and training probes on the 8 layer model takes about 10 minutes on an RTX 3050. The repo also includes scripts for performing board state interventions and skill interventions, along with useful links to open-source code, models, datasets, and pretrained models.

The vscode-pddl extension provides comprehensive support for Planning Domain Description Language (PDDL) in Visual Studio Code. It enables users to model planning domains, validate them, industrialize planning solutions, and run planners. The extension offers features like syntax highlighting, auto-completion, plan visualization, plan validation, plan happenings evaluation, search debugging, and integration with Planning.Domains. Users can create PDDL files, run planners, visualize plans, and debug search algorithms efficiently within VS Code.

Motia is an AI agent framework designed for software engineers to create, test, and deploy production-ready AI agents quickly. It provides a code-first approach, allowing developers to write agent logic in familiar languages and visualize execution in real-time. With Motia, developers can focus on business logic rather than infrastructure, offering zero infrastructure headaches, multi-language support, composable steps, built-in observability, instant APIs, and full control over AI logic. Ideal for building sophisticated agents and intelligent automations, Motia's event-driven architecture and modular steps enable the creation of GenAI-powered workflows, decision-making systems, and data processing pipelines.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

PandaAI is a Python platform that enables users to interact with their data in natural language, catering to both non-technical and technical users. It simplifies data querying and analysis, offering conversational data analytics capabilities with minimal code. Users can ask questions, visualize charts, and compare dataframes effortlessly. The tool aims to streamline data exploration and decision-making processes by providing a user-friendly interface for data manipulation and analysis.

AIDE is a machine learning code generation agent that can generate solutions for machine learning tasks from natural language descriptions. It has the following features: 1. **Instruct with Natural Language**: Describe your problem or additional requirements and expert insights, all in natural language. 2. **Deliver Solution in Source Code**: AIDE will generate Python scripts for the **tested** machine learning pipeline. Enjoy full transparency, reproducibility, and the freedom to further improve the source code! 3. **Iterative Optimization**: AIDE iteratively runs, debugs, evaluates, and improves the ML code, all by itself. 4. **Visualization**: We also provide tools to visualize the solution tree produced by AIDE for a better understanding of its experimentation process. This gives you insights not only about what works but also what doesn't. AIDE has been benchmarked on over 60 Kaggle data science competitions and has demonstrated impressive performance, surpassing 50% of Kaggle participants on average. It is particularly well-suited for tasks that require complex data preprocessing, feature engineering, and model selection.

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 |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

The 'awesome-air-quality' repository is a curated list of software libraries, tools, and resources related to air quality data acquisition, analysis, and visualization. It includes libraries in various programming languages such as Python, Java, R, and C#, as well as hardware drivers and software for gas sensors and particulate matter sensors. The repository aims to provide a comprehensive collection of tools for working with air quality data from different sources and for different purposes.

KaibanJS is a JavaScript-native framework for building multi-agent AI systems. It enables users to create specialized AI agents with distinct roles and goals, manage tasks, and coordinate teams efficiently. The framework supports role-based agent design, tool integration, multiple LLMs support, robust state management, observability and monitoring features, and a real-time agentic Kanban board for visualizing AI workflows. KaibanJS aims to empower JavaScript developers with a user-friendly AI framework tailored for the JavaScript ecosystem, bridging the gap in the AI race for non-Python developers.

MarkLLM is an open-source toolkit designed for watermarking technologies within large language models (LLMs). It simplifies access, understanding, and assessment of watermarking technologies, supporting various algorithms, visualization tools, and evaluation modules. The toolkit aids researchers and the community in ensuring the authenticity and origin of machine-generated text.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

Shows year progress and safeguards tech details.

Guides software development processes through Kanban methodologies.

Creates schedules, charts, or graphs based on user inputs.

I craft visuals for medical concepts.

Visualize and inform on bouquets.

This GPT will help you set and visualize an intention for a spiritual ceremony

Visualize & learn about history

I'm an interior decorator using DALL-E 3 to visualize your space's potential.

Visualize D&D adventures with stunning, lore-accurate art. Huzzah!

A film director helping to visualize scripts into storyboards.

Helps character artists visualize items for characters with photo-realistic images.

Visualize your dreams at night.밤에 꾼 꿈을 시각화 해드립니다..จินตนาการความฝันของคุณในเวลากลางคืน.夜の夢を視覚化する.रात में अपने सपनों को दिखाएं.Hãy hình dung giấc mơ của bạn vào ban đêm.Bayangkan mimpimu di malam hari.在夜間可視化您的夢境

I craft and visualize 'what if' histories.

I craft and visualize 2x2 strategy frameworks.

A guide to visualize and manifest your desires through the Law of Attraction.

International Time Zone Meeting Planner / Converter (independently verify info received). Meet your AI assistant for managing international time zones, specializing in coordinating meetings & events across different regions. Effortlessly plan & visualize physical & digital global engagements.

I guide chess strategy and visualize board states.

Explore & interpret the Eurostat database. Type in requests for statistics, also ask to visualize it. Works best wish specific datasets. It's meant for professionals familiar with the Eurostat database looking for a faster way to explore it.

Master the art of Google Sheets with an assistant who can do everything from answer questions about basic features, explain functions in an eloquent and succinct manner, simplify the most complex formulas into easy steps, and help you identify techniques to effectively visualize your data.

InsightArt is your compassionate art therapy guide, leveraging the power of DALL-E 3 to create and interpret artworks that mirror your emotional journey. It's here to help you visualize and explore your feelings, offering a unique blend of artistic creativity and therapeutic insight.