Best AI tools for< Visualize Training Results >

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.

Blackshark.ai is an AI-based platform that generates real-time accurate semantic photorealistic 3D digital twin of the entire planet. The platform extracts insights about the planet's infrastructure from satellite and aerial imagery using machine learning at a global scale. It provides a photorealistic, geo-typical, or asset-specific digital twin for visualization, simulation, mapping, mixed reality environments, and other enterprise solutions. The platform offers features such as 3D Semantic Map, Synthetic Environments, ORCA™HUNTR for object identification, SYNTH3D for 3D replica of the planet's surface, Digital Airports, Synthetic Training Data, Semantic 3D City Models, and Geospatial Analytics.

SkyHive is an AI-powered platform that aims to organize the world's workforce data and facilitate reskilling. It offers solutions for businesses, governments, educators, and individuals to leverage skills-based models, automate processes, and drive employee engagement. SkyHive's technology utilizes advanced skills matching algorithms, real-time labor market data, and predictive analytics to help users identify skill gaps, connect to opportunities, and accelerate career advancement.

Comet ML is an extensible, fully customizable machine learning platform that aims to move ML forward by supporting productivity, reproducibility, and collaboration. It integrates with existing infrastructure and tools to manage, visualize, and optimize models from training runs to production monitoring. Users can track and compare training runs, create a model registry, and monitor models in production all in one platform. Comet's platform can be run on any infrastructure, enabling users to reshape their ML workflow and bring their existing software and data stack.

DecorAI.xyz is an AI-driven interior design tool that allows users to generate dream rooms using artificial intelligence. By simply taking a picture of a room, users can see how it looks in different themes and receive personalized design suggestions. With exceptional training on a massive dataset of 160 million design samples, DecorAI optimizes spatial layouts, provides cost-effective design solutions, and saves time compared to traditional interior design methods. The tool caters to homeowners, renters, and small businesses looking to redesign their spaces without the need for an expensive interior designer.

Data Science Dojo is a globally recognized e-learning platform that offers programs in data science, data analytics, machine learning, and more. They provide comprehensive and hands-on training in various formats such as in-person, virtual instructor-led, and self-paced training. The focus is on helping students develop a think-business-first mindset to apply their data science skills effectively in real-world scenarios. With over 2500 enterprises trained, Data Science Dojo aims to make data science accessible to everyone.

DVC Studio is a collaboration tool for machine learning teams. It provides seamless data and model management, experiment tracking, visualization, and automation. DVC Studio is built for ML researchers, practitioners, and managers. It enables model organization and discovery across all ML projects and manages model lifecycle with Git, unifying ML projects with the best DevOps practices. DVC Studio also provides ML experiment tracking, visualization, collaboration, and automation using Git. It applies software engineering and DevOps best-practices to automate ML bookkeeping and model training, enabling easy collaboration and faster iterations.

Weights & Biases is a machine learning platform that helps data scientists and engineers build, train, and deploy machine learning models. It provides a central location to track and manage all of your machine learning projects, and it offers a variety of tools to help you collaborate with others and share your work.

Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.

Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.

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 from text prompts or screenshots, create themes, and transform hand-drawn sketches into digital designs. Uizard empowers product teams to visualize, communicate, and iterate on design concepts quickly and efficiently, making it an essential tool for designers, product managers, marketers, and developers.

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.

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.

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.

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.

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.

Visuali is an AI-powered generative art tool that allows users to turn their imagination into reality. With Visuali, users can create stunning images and videos from scratch, or they can use Visuali's pre-trained models to generate unique and inspiring content. Visuali is perfect for artists, designers, and anyone who wants to explore the possibilities of AI-generated art.

FutureKid.ai is an AI-powered application that allows users to generate pictures of their future kids using just one image of each parent. The application uses advanced AI algorithms to create realistic HD images that provide a glimpse into the user's future family. The process is automated, ensuring user privacy by deleting all data from servers within 24 hours. FutureKid.ai is a German-based company that values user privacy and offers a unique way to visualize potential future offspring.

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.

Neptune is a scalable experiment tracker for teams training foundation models. Log millions of runs, effortlessly monitor and visualize model training, and deploy on your infrastructure. Track 100% of metadata to accelerate AI breakthroughs. Log and display any framework and metadata type from any ML pipeline. Organize experiments with nested structures and custom dashboards. Compare results, visualize training, and optimize models quicker. Version models, review stages, and access production-ready models. Share results, manage users, and projects. Integrate with 25+ frameworks. Trusted by great companies to improve workflow.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

ReproModel is an open-source toolbox designed to boost AI research efficiency by enabling researchers to reproduce, compare, train, and test AI models faster. It provides standardized models, dataloaders, and processing procedures, allowing researchers to focus on new datasets and model development. With a no-code solution, users can access benchmark and SOTA models and datasets, utilize training visualizations, extract code for publication, and leverage an LLM-powered automated methodology description writer. The toolbox helps researchers modularize development, compare pipeline performance reproducibly, and reduce time for model development, computation, and writing. Future versions aim to facilitate building upon state-of-the-art research by loading previously published study IDs with verified code, experiments, and results stored in the system.

DL3DV-10K is a large-scale dataset of real-world scene-level videos with annotations, covering diverse scenes with different levels of reflection, transparency, and lighting. It includes 10,510 multi-view scenes with 51.2 million frames at 4k resolution, and offers benchmark videos for novel view synthesis (NVS) methods. The dataset is designed to facilitate research in deep learning-based 3D vision and provides valuable insights for future research in NVS and 3D representation learning.

Nitrain is a framework for medical imaging AI that provides tools for sampling and augmenting medical images, training models on medical imaging datasets, and visualizing model results in a medical imaging context. It supports using pytorch, keras, and tensorflow.

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.

Forust is a lightweight package for building gradient boosted decision tree ensembles. The algorithm code is written in Rust with a Python wrapper. It implements the same algorithm as XGBoost and provides nearly identical results. The package was developed to better understand XGBoost, as a fun project in Rust, and to experiment with adding new features to the algorithm in a simpler codebase. Forust allows training gradient boosted decision tree ensembles with multiple objective functions, predicting on datasets, inspecting model structures, calculating feature importance, and saving/loading trained boosters.

Uncheatable Eval is a tool designed to assess the language modeling capabilities of LLMs on real-time, newly generated data from the internet. It aims to provide a reliable evaluation method that is immune to data leaks and cannot be gamed. The tool supports the evaluation of Hugging Face AutoModelForCausalLM models and RWKV models by calculating the sum of negative log probabilities on new texts from various sources such as recent papers on arXiv, new projects on GitHub, news articles, and more. Uncheatable Eval ensures that the evaluation data is not included in the training sets of publicly released models, thus offering a fair assessment of the models' performance.

Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.

Sematic is an open-source ML development platform that allows ML Engineers and Data Scientists to write complex end-to-end pipelines with Python. It can be executed locally, on a cloud VM, or on a Kubernetes cluster. Sematic enables chaining data processing jobs with model training into reproducible pipelines that can be monitored and visualized in a web dashboard. It offers features like easy onboarding, local-to-cloud parity, end-to-end traceability, access to heterogeneous compute resources, and reproducibility.

Open-Source Evaluation for LLM Applications. `continuous-eval` is an open-source package created for granular and holistic evaluation of GenAI application pipelines. It offers modularized evaluation, a comprehensive metric library covering various LLM use cases, the ability to leverage user feedback in evaluation, and synthetic dataset generation for testing pipelines. Users can define their own metrics by extending the Metric class. The tool allows running evaluation on a pipeline defined with modules and corresponding metrics. Additionally, it provides synthetic data generation capabilities to create user interaction data for evaluation or training purposes.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

KaTrain is a tool designed for analyzing games and playing go with AI feedback from KataGo. Users can review their games to find costly moves, play against AI with immediate feedback, play against weakened AI versions, and generate focused SGF reviews. The tool provides various features such as previews, tutorials, installation instructions, and configuration options for KataGo. Users can play against AI, receive instant feedback on moves, explore variations, and request in-depth analysis. KaTrain also supports distributed training for contributing to KataGo's strength and training bigger models. The tool offers themes customization, FAQ section, and opportunities for support and contribution through GitHub issues and Discord community.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

FarmVibes.AI is a repository focused on developing multi-modal geospatial machine learning models for agriculture and sustainability. It enables users to fuse various geospatial and spatiotemporal datasets, such as satellite imagery, drone imagery, and weather data, to generate robust insights for agriculture-related problems. The repository provides fusion workflows, data preparation tools, model training notebooks, and an inference engine to facilitate the creation of geospatial models tailored for agriculture and farming. Users can interact with the tools via a local cluster, REST API, or a Python client, and the repository includes documentation and notebook examples to guide users in utilizing FarmVibes.AI for tasks like harvest date detection, climate impact estimation, micro climate prediction, and crop identification.

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. |  |

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.

This is a brief generator, it will help generate ideas for your new art. It will follow your prompts and in the end will provide a description of the art, visualize it, provide a color palette and RGB code to it. Also, make a ready to use prompt for MidJourney. Have fun!

Charming coffee visualiser

Expert in visualizing industrial designs via DALL-E