Best AI tools for< Analyze Models >

MobiHealthNews is a digital health publication that covers breaking news and trends in healthcare. The website provides insights on AI models in radiology, responsible AI implementation, and digital tools for mental health. It also features news on partnerships in healthcare technology and advancements in AI adoption. MobiHealthNews aims to deliver daily updates on the latest developments in digital health and AI applications.

Susterra is an advanced analytics platform for Public Finance stakeholders, aiming to catalyze urban development by providing powerful insights. The platform integrates leading practices from academia, leverages public data growth, and utilizes technology innovations like ML and AI to enable issuers to make suitable choices for accelerating the development of Smart Cities across the United States. Susterra offers state-of-the-art analytics, including TerraScore, TerraVision, TerraView, and Impact IQ, with a focus on public program evaluation and data visualization tools for various sectors such as Utilities, Education, Healthcare, and more.

xAI Grok is a visual analytics platform that helps users understand and interpret machine learning models. It provides a variety of tools for visualizing and exploring model data, including interactive charts, graphs, and tables. xAI Grok also includes a library of pre-built visualizations that can be used to quickly get started with model analysis.

Cogniflow is a no-code AI platform that allows users to build and deploy custom AI models without any coding experience. The platform provides a variety of pre-built AI models that can be used for a variety of tasks, including customer service, HR, operations, and more. Cogniflow also offers a variety of integrations with other applications, making it easy to connect your AI models to your existing workflow.

Stocked is an AI-powered stock advisory service that provides monthly stock recommendations to help investors build a portfolio that outperforms the S&P 500. The service uses machine learning models to analyze terabytes of data and identify stocks with the highest potential for growth. Stocked is designed for buy-and-hold investors who are looking to significantly grow their portfolio over long periods of time.

Epoch AI is a research institute dedicated to investigating key trends and questions that will shape the trajectory and governance of AI. They provide essential insights for policymakers, conduct rigorous analysis of trends in AI and machine learning, and produce reports, papers, models, and visualizations to advance evidence-based discussions about AI. Epoch AI collaborates with stakeholders and collects key data on machine learning models to analyze historical and contemporary progress in AI. They are known for their thoughtful and best-researched survey work in the industry.

GetWebsite.Report is an innovative web service that leverages state-of-the-art AI models to analyze and optimize landing pages across five main categories: user interface, user experience, visual design, content, and SEO. It provides actionable insights to enhance the performance and effectiveness of digital presence. The tool offers personalized recommendations to improve conversion rates, SEO, usability, and messaging. It is rated 4.8/5 by 290+ users and comes with a 100% money-back guarantee if not satisfied. GetWebsite.Report is designed to be adaptable across diverse industries, offering practical advice and resources for optimizing user experience and search visibility.

Centa is an AI-powered calorie counter application that simplifies tracking calories and macros by allowing users to take a photo of their meal or describe it. The app utilizes cutting-edge AI models to analyze the food items, portions, and nutritional information. Centa offers a user-friendly experience for individuals looking to monitor their diet effortlessly and accurately. With features like unlimited scans, accurate calorie estimation, and compatibility with homemade meals, Centa is a convenient tool for maintaining a healthy lifestyle.

AdGen AI is an AI-powered creative generator that helps businesses create high-performing ad copy and visuals for multiple ad channels. It uses machine learning models to analyze product data and generate a variety of ad creatives that are tailored to the target audience. AdGen AI also allows users to publish ads directly from the platform, making it easy to launch and manage ad campaigns.

ClimateAi is an AI-powered platform that helps businesses in the food and agriculture industry to minimize climate risk and maximize future opportunities. The platform utilizes AI and patented models to analyze climate and weather data from various sources, providing actionable insights to users across the value chain. ClimateAi enables users to make informed decisions, adapt operations, source smarter, and invest confidently without requiring data science expertise.

Simpleem is an Artificial Emotional Intelligence (AEI) tool that helps users uncover intentions, predict success, and leverage behavior for successful interactions. By measuring all interactions and correlating them with concrete outcomes, Simpleem provides insights into verbal, para-verbal, and non-verbal cues to enhance customer relationships, track customer rapport, and assess team performance. The tool aims to identify win/lose patterns in behavior, guide users on boosting performance, and prevent burnout by promptly identifying red flags. Simpleem uses proprietary AI models to analyze real-world data and translate behavioral insights into concrete business metrics, achieving a high accuracy rate of 94% in success prediction.

PredictModel is an AI tool that specializes in creating custom Machine Learning models tailored to meet unique requirements. The platform offers a comprehensive three-step process, including generating synthetic data, training ML models, and deploying them to AWS. PredictModel helps businesses streamline processes, improve customer segmentation, enhance client interaction, and boost overall business performance. The tool maximizes accuracy through customized synthetic data generation and saves time and money by providing expert ML engineers. With a focus on automated lead prioritization, fraud detection, cost optimization, and planning, PredictModel aims to stay ahead of the curve in the ML industry.

Groq is a fast AI inference tool that offers instant intelligence for openly-available models like Llama 3.1. It provides ultra-low-latency inference for cloud deployments and is compatible with other providers like OpenAI. Groq's speed is proven to be instant through independent benchmarks, and it powers leading openly-available AI models such as Llama, Mixtral, Gemma, and Whisper. The tool has gained recognition in the industry for its high-speed inference compute capabilities and has received significant funding to challenge established players like Nvidia.

PromptLoop is an AI-powered tool that integrates with Excel and Google Sheets to enhance market research and data analysis. It offers custom AI models tailored to specific needs, enabling users to extract insights from complex information. With PromptLoop, users can leverage advanced AI capabilities for tasks such as web research, content analysis, and data labeling, streamlining workflows and improving efficiency.

aimlapi.com is an AI tool that offers 100+ AI models accessible via one API. It provides developers with a wide range of AI models for various tasks such as chat, language, image generation, and code processing. The platform is designed to be user-friendly, cost-efficient, and scalable, making it suitable for developers of all levels. With a focus on transparency, affordability, and compatibility with OpenAI, aimlapi.com aims to provide high-quality AI solutions to its users.

thisorthis.ai is an AI tool that allows users to compare generative AI models and AI model responses. It helps users analyze and evaluate different AI models to make informed decisions. The tool requires JavaScript to be enabled for optimal functionality.

Julius AI is an advanced AI data analyst tool that allows users to analyze data with computational AI, chat with files to get expert-level insights, create sleek data visualizations, perform modeling and predictive forecasting, solve math, physics, and chemistry problems, generate polished analyses and summaries, save time by automating data work, and unlock statistical modeling without complexity. It offers features like generating visualizations, asking data questions, effortless cleaning, instant data export, creating animations, and supercharging data analysis. Julius AI is loved by over 1,200,000 users worldwide and is designed to help knowledge workers make the most out of their data.

Qwen is an AI tool that focuses on developing and releasing various language models, including dense models, coding models, mathematical models, and vision language models. The Qwen family offers open-source models with different parameter ranges to cater to various user needs, such as production use, mobile applications, coding assistance, mathematical problem-solving, and visual understanding of images and videos. Qwen aims to enhance intelligence and provide smarter and more knowledgeable models for developers and users.

Fiddler AI is an AI Observability platform that provides tools for monitoring, explaining, and improving the performance of AI models. It offers a range of capabilities, including explainable AI, NLP and CV model monitoring, LLMOps, and security features. Fiddler AI helps businesses to build and deploy high-performing AI solutions at scale.

Aicado.ai is an AI tool that provides comprehensive comparisons and insights into various AI models such as GPT-4, Llama, Gemini, and more. Users can access detailed reviews and features to find the best AI model for their specific needs. The platform offers a premium dashboard for in-depth analysis and comparison of different AI models.

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

**RVC_CLI: Retrieval-based Voice Conversion Command Line Interface** This command-line interface (CLI) provides a comprehensive set of tools for voice conversion, enabling you to modify the pitch, timbre, and other characteristics of audio recordings. It leverages advanced machine learning models to achieve realistic and high-quality voice conversions. **Key Features:** * **Inference:** Convert the pitch and timbre of audio in real-time or process audio files in batch mode. * **TTS Inference:** Synthesize speech from text using a variety of voices and apply voice conversion techniques. * **Training:** Train custom voice conversion models to meet specific requirements. * **Model Management:** Extract, blend, and analyze models to fine-tune and optimize performance. * **Audio Analysis:** Inspect audio files to gain insights into their characteristics. * **API:** Integrate the CLI's functionality into your own applications or workflows. **Applications:** The RVC_CLI finds applications in various domains, including: * **Music Production:** Create unique vocal effects, harmonies, and backing vocals. * **Voiceovers:** Generate voiceovers with different accents, emotions, and styles. * **Audio Editing:** Enhance or modify audio recordings for podcasts, audiobooks, and other content. * **Research and Development:** Explore and advance the field of voice conversion technology. **For Jobs:** * Audio Engineer * Music Producer * Voiceover Artist * Audio Editor * Machine Learning Engineer **AI Keywords:** * Voice Conversion * Pitch Shifting * Timbre Modification * Machine Learning * Audio Processing **For Tasks:** * Convert Pitch * Change Timbre * Synthesize Speech * Train Model * Analyze Audio

LLM Hallucination Index - RAG Special is a comprehensive evaluation of large language models (LLMs) focusing on context length and open vs. closed-source attributes. The index explores the impact of context length on model performance and tests the assumption that closed-source LLMs outperform open-source ones. It also investigates the effectiveness of prompting techniques like Chain-of-Note across different context lengths. The evaluation includes 22 models from various brands, analyzing major trends and declaring overall winners based on short, medium, and long context insights. Methodologies involve rigorous testing with different context lengths and prompting techniques to assess models' abilities in handling extensive texts and detecting hallucinations.

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

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.

Foundations-of-LLMs is a comprehensive book aimed at readers interested in large language models, providing systematic explanations of foundational knowledge and introducing cutting-edge technologies. The book covers traditional language models, evolution of large language model architectures, prompt engineering, parameter-efficient fine-tuning, model editing, and retrieval-enhanced generation. Each chapter uses an animal as a theme to explain specific technologies, enhancing readability. The content is based on the author team's exploration and understanding of the field, with continuous monthly updates planned. The book includes a 'Paper List' for each chapter to track the latest advancements in related technologies.

This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.

LLM-Viewer is a tool for visualizing Language and Learning Models (LLMs) and analyzing performance on different hardware platforms. It enables network-wise analysis, considering factors such as peak memory consumption and total inference time cost. With LLM-Viewer, users can gain valuable insights into LLM inference and performance optimization. The tool can be used in a web browser or as a command line interface (CLI) for easy configuration and visualization. The ongoing project aims to enhance features like showing tensor shapes, expanding hardware platform compatibility, and supporting more LLMs with manual model graph configuration.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Llama-github is a powerful tool that helps retrieve relevant code snippets, issues, and repository information from GitHub based on queries. It empowers AI agents and developers to solve coding tasks efficiently. With features like intelligent GitHub retrieval, repository pool caching, LLM-powered question analysis, and comprehensive context generation, llama-github excels at providing valuable knowledge context for development needs. It supports asynchronous processing, flexible LLM integration, robust authentication options, and logging/error handling for smooth operations and troubleshooting. The vision is to seamlessly integrate with GitHub for AI-driven development solutions, while the roadmap focuses on empowering LLMs to automatically resolve complex coding tasks.

Netron is a viewer for neural network, deep learning and machine learning models. It supports a wide range of model formats, including ONNX, TensorFlow Lite, Core ML, Keras, Caffe, Darknet, MXNet, PaddlePaddle, ncnn, MNN and TensorFlow.js. Netron also has experimental support for PyTorch, TorchScript, TensorFlow, OpenVINO, RKNN, MediaPipe, ML.NET and scikit-learn.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

ChatAFL is a protocol fuzzer guided by large language models (LLMs) that extracts machine-readable grammar for protocol mutation, increases message diversity, and breaks coverage plateaus. It integrates with ProfuzzBench for stateful fuzzing of network protocols, providing smooth integration. The artifact includes modified versions of AFLNet and ProfuzzBench, source code for ChatAFL with proposed strategies, and scripts for setup, execution, analysis, and cleanup. Users can analyze data, construct plots, examine LLM-generated grammars, enriched seeds, and state-stall responses, and reproduce results with downsized experiments. Customization options include modifying fuzzers, tuning parameters, adding new subjects, troubleshooting, and working on GPT-4. Limitations include interaction with OpenAI's Large Language Models and a hard limit of 150,000 tokens per minute.

Trinity is an Explainable AI (XAI) Analysis and Visualization tool designed for Deep Learning systems or other models performing complex classification or decoding. It provides performance analysis through interactive 3D projections that are hyper-dimensional aware, allowing users to explore hyperspace, hypersurface, projections, and manifolds. Trinity primarily works with JSON data formats and supports the visualization of FeatureVector objects. Users can analyze and visualize data points, correlate inputs with classification results, and create custom color maps for better data interpretation. Trinity has been successfully applied to various use cases including Deep Learning Object detection models, COVID gene/tissue classification, Brain Computer Interface decoders, and Large Language Model (ChatGPT) Embeddings Analysis.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

ExplainableAI.jl is a Julia package that implements interpretability methods for black-box classifiers, focusing on local explanations and attribution maps in input space. The package requires models to be differentiable with Zygote.jl. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Users can analyze and visualize explanations for model predictions, with support for different XAI methods and customization. The package aims to provide transparency and insights into model decision-making processes, making it a valuable tool for understanding and validating machine learning models.

llm-colosseum is a tool designed to evaluate Language Model Models (LLMs) in real-time by making them fight each other in Street Fighter III. The tool assesses LLMs based on speed, strategic thinking, adaptability, out-of-the-box thinking, and resilience. It provides a benchmark for LLMs to understand their environment and take context-based actions. Users can analyze the performance of different LLMs through ELO rankings and win rate matrices. The tool allows users to run experiments, test different LLM models, and customize prompts for LLM interactions. It offers installation instructions, test mode options, logging configurations, and the ability to run the tool with local models. Users can also contribute their own LLM models for evaluation and ranking.

ContextCite is a tool for attributing statements generated by LLMs back to specific parts of the context. It allows users to analyze and understand the sources of information used by language models in generating responses. By providing attributions, users can gain insights into how the model makes decisions and where the information comes from.

Learn and design sustainable tokenomics

This prompt is designed to act as an expert psychologist in personality analysis, using three different psychological models: the Big Five Factor model, the Myers-Briggs Sixteen Types model, and the Enneagram model.

This GPT, fueled by NABARD's insights, transforms rural lending in India with custom models, better risk assessments, policy guidance, rural-specific financial products, and financial literacy support, aiming to enhance accessibility and growth in rural economies.

A financial expert building optimized macroeconomic models from a renowned book.

Helps find and analyze ML papers, focusing on SOTA comparisons.

This GPT reviews business plans and pitch decks—Please note: This GPT does NOT share information for training in GPT models. It is responsible for assigning scores and providing feedback based on key criteria such as team background, financial projections, as well as conducting sentiment analysis.

是一个专门用于建立数学模型并撰写python代码的gpt.

Guía paso a paso para la creación y mejora de modelos de negocio usando la metodología Business Model Canvas.

专注于IP和公私域商业模式，提供流量和变现的一站式解决方案。

A friendly data science coach offering practical, useful, and accurate advice.

Interactive ML/AI tutor providing structured daily lessons.

I'm your Machine Learning and Python mentor, ready to teach and guide you.

Salam mən Alas Academy-nin Data Analitika üzrə Süni İntellekt mentoruyam. Mənə istənilən sualı verə bilərsiniz :)

I am a digital scientist skilled in Python, here to assist with scientific and data analysis tasks.

Simplifies data science for professionals.

Multilingual support in Global Economics & Finance studies.

Expert guide on VASP, including online references

AI Assists in learning and troubleshooting Ladybug Tools.

Adaptable facetorch expert, tailoring responses to user expertise.

A biophysicist assistant offering insights into the physics of living systems.