Best AI tools for< Predict Size >

HeyBeauty is an innovative AI-driven platform that revolutionizes the online shopping experience by offering a virtual dressing room powered by cutting-edge artificial intelligence technology. Users can try on clothes digitally, receive personalized style recommendations, and benefit from accurate size predictions, all from the comfort of their homes. HeyBeauty aims to make online shopping interactive, convenient, and tailored to individual preferences.

yPredict.ai is a cutting-edge crypto research and trading platform that offers traders access to numerous AI-powered crypto analysis tools. The platform provides accurate predictions and forecasts for various cryptocurrencies, helping users make informed investment decisions. With a focus on prediction accuracy, yPredict.ai aims to assist both novice and experienced traders in navigating the volatile cryptocurrency market.

Session AI is an in-session marketing platform that helps businesses convert anonymous visitors into customers. It uses AI to predict purchase intent and deliver real-time actions that drive conversions. Session AI can be used by businesses of all sizes in a variety of industries, including retail, travel, and hospitality.

Groundsales.ai is an AI-driven sales forecasting tool that empowers businesses to make accurate predictions and optimize sales strategies. By leveraging advanced analytics and scenario modeling, the platform provides real-time insights and trend analysis to help businesses stay ahead in the competitive market. With seamless data integration and a user-friendly interface, Groundsales.ai offers a data-driven evolution for businesses of all sizes, enabling them to make informed decisions and maximize revenue potential.

Graphite Note is a no-code AI tool that helps businesses transform data into key drivers, predictions, and next-best actions. It is designed to be user-friendly and accessible to businesses of all sizes, even those without a data science team. With Graphite Note, businesses can quickly and easily generate AI models, understand patterns in their data, predict future outcomes, and get actionable insights. This can help businesses make better decisions, improve their operations, and grow their revenue.

Matey AI is an advanced AI application designed to empower legal teams with cutting-edge AI technologies for document classification, document review, outcome prediction, automated trial preparation, and more. The platform leverages AI expertise and legal expertise to provide efficient solutions for legal practices of all sizes, ensuring data security, compliance, and seamless integration with existing legal workflows.

Mindful AI Media is a platform offering AI-powered tools and digital solutions to optimize business operations. They provide customized solutions for businesses of all sizes, focusing on innovation, integrity, and empathy. The platform offers products like Business App Pro, Grand Central AI, and Inbox Pro to help businesses streamline operations, enhance customer experience, and drive growth. Mindful AI Media aims to empower businesses through cutting-edge technology and ethical use of data.

AnO is an AI-powered Marketing Technology consulting company that specializes in providing digital transformation services for businesses of all sizes. They offer comprehensive marketing services, including Strategy Development, Customer Engagement Platforms (CDP), CRM Effectiveness, AI Marketing, and complete outsourced marketing solutions. AnO is committed to staying at the forefront of technological advancements and industry best practices to deliver cutting-edge solutions that drive sustainable growth and competitive advantage for their clients.

Cohere is a leading provider of artificial intelligence (AI) tools and services. Our mission is to make AI accessible and useful to everyone, from individual developers to large enterprises. We offer a range of AI tools and services, including natural language processing, computer vision, and machine learning. Our tools are used by businesses of all sizes to improve customer service, automate tasks, and gain insights from data.

Inventoro is a smart inventory forecasting and replenishment tool that helps businesses optimize their inventory management processes. By analyzing past sales data, the tool predicts future sales, recommends order quantities, reduces inventory size, identifies profitable inventory items, and ensures customer satisfaction by avoiding stockouts. Inventoro offers features such as sales forecasting, product segmentation, replenishment, system integration, and forecast automations. The tool is designed to help businesses decrease inventory, increase revenue, save time, and improve product availability. It is suitable for businesses of all sizes and industries looking to streamline their inventory management operations.

Cat Identifier is an AI-based application that helps users identify cat breeds by providing an image or video of a cat. The app predicts the breed of the cat and offers detailed information about its characteristics, temperament, and history. With a database of over 170+ cat breeds, users can learn about each breed's personality, energy level, size, and grooming requirements to make informed decisions. Additionally, the app features Cat Finder to suggest the best cat breeds based on user preferences, Cat Feed Listing for daily predictions and fun facts, and Cat Mood Detection to analyze a cat's mood through facial expressions and body language.

The Predict API is a powerful tool that allows you to forecast your data with simplicity and accuracy. It uses the latest advancements in stochastic modeling and machine learning to provide you with reliable projections. The API is easy to use and can be integrated with any application. It is also highly scalable, so you can use it to forecast large datasets. With the Predict API, you can gain valuable insights into your data and make better decisions.

AI Baby Generator is an AI application that predicts what your future child will look like based on parent photos and features. It uses advanced AI technology to generate hyper-realistic baby photos with a high facial match rate. The application offers different packages with varying features, including personalized baby photos at different ages, personality descriptions, and high-quality images delivered within 24 hours. Users can upload photos of themselves or celebrities to see what their future baby might look like. The service is for entertainment purposes only and does not provide medical or predictive information.

Numerai is a data science tournament platform where users can compete to build models that predict the stock market. The platform provides users with clean and regularized hedge fund quality data, and users can build models using Python or R scripts. Numerai also has a cryptocurrency, NMR, which users can stake on their models to earn rewards.

Neurons is a platform that uses AI to predict consumer responses and behavior. It offers a variety of solutions for businesses, including marketing agencies, designers, and e-commerce companies. Neurons' AI-powered tools can help businesses optimize their marketing campaigns, improve their product design, and better understand their customers.

BforeAI is an AI-powered platform that specializes in fighting cyberthreats with intelligence. The platform offers predictive security solutions to prevent phishing, spoofing, impersonation, hijacking, ransomware, online fraud, and data exfiltration. BforeAI uses cutting-edge AI technology for behavioral analysis and predictive results, going beyond reactive blocklists to predict and prevent attacks before they occur. The platform caters to various industries such as financial, manufacturing, retail, and media & entertainment, providing tailored solutions to address unique security challenges.

Heatseeker is an AI-powered market experimentation tool that helps businesses predict customer preferences, conduct feature tests, and generate value propositions. It enables users to answer critical growth questions about market, audience, and product features through AI-powered experiments. Heatseeker provides insights into market trends, competitor analysis, and helps in making data-driven decisions. The platform offers curated recommendations, competitive intelligence, and continuous testing for refining strategies. It automates ad campaign generation, data collection, and provides recommendations for launching new products. Heatseeker is designed to help businesses optimize their marketing efforts and improve their product offerings.

ClosedLoop is a healthcare data science platform that helps organizations improve outcomes and reduce costs by providing accurate, explainable, and actionable predictions of individual-level health risks. The platform offers predictive analytics for various healthcare sectors, data science automation, and a healthcare content library to accelerate time to value. ClosedLoop's AI/ML platform is designed exclusively for the data science needs of modern healthcare organizations, enabling proactive interventions, improved clinical outcomes, and innovative healthcare offerings.

AutoPredict is an AI application that predicts how long a car will last by analyzing over 100 million data points. It offers accurate estimates of a car's life span, providing users with valuable insights based on statistical analysis. The application also provides an API for integrating predictions and statistics into other businesses. AutoPredict Blog shares insights and statistics discovered during the development of their AI model.

Lotto Chart is a highly accurate AI-powered chart for predicting lottery numbers. It harnesses the power of artificial intelligence, statistical analysis, and probability to generate winning combinations for various lotteries. The application processes billions of data points, utilizes 7 powerful prediction models, and provides advanced data-driven predictions to help users increase their chances of winning. Lotto Chart also offers support for seeded predictions, daily updated insights and reports, and tools to easily identify patterns and trends in lottery numbers.

LLM-Blender is a framework for ensembling large language models (LLMs) to achieve superior performance. It consists of two modules: PairRanker and GenFuser. PairRanker uses pairwise comparisons to distinguish between candidate outputs, while GenFuser merges the top-ranked candidates to create an improved output. LLM-Blender has been shown to significantly surpass the best LLMs and baseline ensembling methods across various metrics on the MixInstruct benchmark dataset.

Alice is an agentic workflow framework that integrates task execution and intelligent chat capabilities. It provides a flexible environment for creating, managing, and deploying AI agents for various purposes, leveraging a microservices architecture with MongoDB for data persistence. The framework consists of components like APIs, agents, tasks, and chats that interact to produce outputs through files, messages, task results, and URL references. Users can create, test, and deploy agentic solutions in a human-language framework, making it easy to engage with by both users and agents. The tool offers an open-source option, user management, flexible model deployment, and programmatic access to tasks and chats.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

Geolocation-OSINT is a repository that provides a comprehensive list of resources, tools, and platforms for geolocation challenges and open-source intelligence. It includes a wide range of mapping services, image search tools, AI-powered geolocation estimators, and satellite imagery archives. The repository covers various aspects of geolocation, from finding GPS coordinates to estimating the size of objects in images. Users can access tools for social media monitoring, street-level imagery, and geospatial analysis. Geolocation-OSINT is a valuable resource for individuals interested in geolocation, mapping, and intelligence gathering.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

AgroTech AI platform is a comprehensive web-based tool where users can access various machine learning models for making accurate predictions related to agriculture. It offers solutions for crop management, soil health assessment, pest control, and more. The platform implements machine learning algorithms to provide functionalities like fertilizer prediction, crop prediction, soil quality prediction, yield prediction, and mushroom edibility prediction.

AlphaFold3 is an implementation of the Alpha Fold 3 model in PyTorch for accurate structure prediction of biomolecular interactions. It includes modules for genetic diffusion and full model examples for forward pass computations. The tool allows users to generate random pair and single representations, operate on atomic coordinates, and perform structure predictions based on input tensors. The implementation also provides functionalities for training and evaluating the model.

PyTorch Forecasting is a PyTorch-based package for time series forecasting with state-of-the-art network architectures. It offers a high-level API for training networks on pandas data frames and utilizes PyTorch Lightning for scalable training on GPUs and CPUs. The package aims to simplify time series forecasting with neural networks by providing a flexible API for professionals and default settings for beginners. It includes a timeseries dataset class, base model class, multiple neural network architectures, multi-horizon timeseries metrics, and hyperparameter tuning with optuna. PyTorch Forecasting is built on pytorch-lightning for easy training on various hardware configurations.

This project explores the capability of Large Language Models (LLMs) to perform regression tasks using in-context examples. It compares the performance of LLMs like GPT-4 and Claude 3 Opus with traditional supervised methods such as Linear Regression and Gradient Boosting. The project provides preprints and results demonstrating the strong performance of LLMs in regression tasks. It includes datasets, models used, and experiments on adaptation and contamination. The code and data for the experiments are available for interaction and analysis.

Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes.

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

Termax is an LLM agent in your terminal that converts natural language to commands. It is featured by: - Personalized Experience: Optimize the command generation with RAG. - Various LLMs Support: OpenAI GPT, Anthropic Claude, Google Gemini, Mistral AI, and more. - Shell Extensions: Plugin with popular shells like `zsh`, `bash` and `fish`. - Cross Platform: Able to run on Windows, macOS, and Linux.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

Netsaur is a powerful machine learning library for Deno, offering a lightweight and easy-to-use neural network solution. It is blazingly fast and efficient, providing a simple API for creating and training neural networks. Netsaur can run on both CPU and GPU, making it suitable for serverless environments. With Netsaur, users can quickly build and deploy machine learning models for various applications with minimal dependencies. This library is perfect for both beginners and experienced machine learning practitioners.

Pipeline is a Python library designed for constructing computational flows for AI/ML models. It supports both development and production environments, offering capabilities for inference, training, and finetuning. The library serves as an interface to Mystic, enabling the execution of pipelines at scale and on enterprise GPUs. Users can also utilize this SDK with Pipeline Core on a private hosted cluster. The syntax for defining AI/ML pipelines is reminiscent of sessions in Tensorflow v1 and Flows in Prefect.

This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.

I predict DAU based on growth and retention.

Predict the future, opine on politics and controversial topics, and have GPT assess what is "true"

I predict future stock market prices. AI analyst. Your trading analysis assistant. Press H to bring up prompt hot key menu. Not financial advice.

Analyze Financial Statements step by step to Predict Earnings Direction

Predict fashion trends

AI expert in analyzing historical patterns to predict future events

Does Pool Performance of Elite Triathletes Predict Open-Water Performance?

A moot competition companion. & Trial Prep companion . Test and improve arguments- predict your opponent's reaction.

Personalized, analytical sports prediction AI.

あなたの顔を予想します

Predicts gender for first names using data

Our college entrance exam prediction app uses advanced algorithms and data analysis to provide accurate predictions for students preparing to take their college entrance exams.

Prédictif des tendances crypto à partir de la presse et des réseaux sociaux

Horoscopes--八字算命术预测你的健康、婚姻、事业、财富...

Analyzes and predicts the SSE 500 Index.

1620年代の主要な歴史的出来事を分析し未来の予測に役立てる。

A question ? Ask me for a prediction ... ( /help for help )

MMA Expert & Trainer

Advanced AI for real-time predictive analysis using machine learning.

Advanced NFL and parlay predictor with comprehensive analysis