Best AI tools for< Forecast Data >

ChatWorks is an AI application that offers tailored AI solutions and expert AI consultancy to elevate businesses to the next level. It provides advanced technology and customized strategies to solve unique challenges. The application automates various processes such as email automation, data analysis, caption generation, and task management, catering to different industries like social media, customer service, construction, and more.

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.

ChartPixel is an AI-assisted data analysis platform that empowers users to effortlessly generate charts, insights, and actionable statistics in just 30 seconds. The platform is designed to demystify data and analysis, making it accessible to users of all skill levels. ChartPixel combines the power of AI with domain expertise to provide secure and reliable output, ensuring trustworthy results without compromising data privacy. With user-friendly features and educational tools, ChartPixel helps users clean, wrangle, visualize, and present data with ease, catering to both beginners and professionals.

Walter Shields Data Academy is an AI-powered platform offering premium training in SQL, Python, and Excel. With over 200,000 learners, it provides curated courses from bestselling books and LinkedIn Learning. The academy aims to revolutionize data expertise and empower individuals to excel in data analysis and AI technologies.

Datarails is a financial planning and analysis platform for Excel users. It automates data consolidation, reporting, and planning while enabling finance teams to continue using their spreadsheets and financial models. With Datarails, finance teams can save time on repetitive tasks and focus on strategic insights that drive business growth.

Datasparq is a specialist AI & data firm that designs, builds, and runs high-impact AI & data solutions. They help businesses at every stage of their AI journey, from value discovery to managing AI solutions. Datasparq combines data science, data engineering, product thinking, and design to deliver valuable, operational AI solutions quickly. Their focus is on creating AI tools that drive business improvements, efficiency, and effectiveness through data platforms, analytics, and machine learning.

Cue is an AI-powered data analytics tool designed to help GTM (Go-To-Market) leaders make informed decisions without the need to be data scientists. It seamlessly embeds data science into organizations, providing measurable growth insights and strategies. Cue offers expert data science, clean data integration, AI-driven analysis, customized GTM solutions, and strategy synthesis. It aims to maximize the value of existing data and people, emphasizing the importance of a solid data foundation for business growth.

Alloy.ai is an omnichannel revenue intelligence platform for consumer brands that helps visualize and analyze sales, supply chain, and forecasting data with full visibility into consumer demand and inventory. The platform connects real-time POS and inventory data from hundreds of retailers, providing a single view of sales and inventory. Alloy.ai uses AI and ML to identify new sales opportunities and potential problems, offering a normalized view of business data for better decision-making.

PandasAI is an open-source AI tool designed for conversational data analysis. It allows users to ask questions in natural language to their enterprise data and receive real-time data insights. The tool is integrated with various data sources and offers enhanced analytics, actionable insights, detailed reports, and visual data representation. PandasAI aims to democratize data analysis for better decision-making, offering enterprise solutions for stable and scalable internal data analysis. Users can also fine-tune models, ingest universal data, structure data automatically, augment datasets, extract data from websites, and forecast trends using AI.

Sherpa.ai is a Federated Learning Platform that enables data collaborations without sharing data. It allows organizations to build and train models with sensitive data from various sources while preserving privacy and complying with regulations. The platform offers enterprise-grade privacy-compliant solutions for improving AI models and fostering collaborations in a secure manner. Sherpa.ai is trusted by global organizations to maximize the value of data and AI, improve results, and ensure regulatory compliance.

Football Predictions AI is a website that provides users with accurate and reliable football match predictions. Users can access a variety of prediction types, including 1x2, BTTS, Over Under, and Correct Score predictions for matches across different leagues. The site also offers live scores, articles, and settings to customize the user experience. With a focus on user privacy and data protection, Football Predictions AI aims to enhance the football betting experience for enthusiasts and fans.

Byterat is a cloud-based platform that provides battery data management, visualization, and analytics. It offers an end-to-end data pipeline that automatically synchronizes, processes, and visualizes materials, manufacturing, and test data from all labs. Byterat also provides 24/7 access to experiments from anywhere in the world and integrates seamlessly with current workflows. It is customizable to specific cell chemistries and allows users to build custom visualizations, dashboards, and analyses. Byterat's AI-powered battery research has been published in leading journals, and its team has pioneered a new class of models that extract tell-tale signals of battery health from electrical signals to forecast future performance.

AskCSV is a revolutionary AI-powered tool that empowers you to unlock valuable insights from your CSV files. Simply ask any question about your data, and AskCSV will provide you with instant, accurate answers and visualizations. Your data remains completely secure, processed directly in your browser's memory without any server uploads. With AskCSV, you can effortlessly analyze your data, identify trends, make informed decisions, and gain a deeper understanding of your business.

JaanchAI is an AI-powered tool that provides valuable insights for e-commerce businesses. It utilizes artificial intelligence algorithms to analyze data and trends in the e-commerce industry, helping businesses make informed decisions to optimize their operations and increase sales. With JaanchAI, users can gain a competitive edge by leveraging advanced analytics and predictive modeling techniques tailored for the e-commerce sector.

Reportify is an AI platform for investment research that provides detailed analysis and insights on various companies, filings, transcripts, reports, and news. Users can explore financial data, performance metrics, and market trends to make informed investment decisions. The platform offers a comprehensive view of the investment landscape, including company histories, financial reports, and industry analysis.

functime is a time-series machine learning tool designed for scalable analysis. It offers a comprehensive set of functions for forecasting, evaluation, and analysis of time-series data. With features like scoring, ranking, and plotting functions, functime simplifies the process of evaluating thousands of forecasts simultaneously. It serves as an AI copilot to help analysts analyze and compare trends, seasonality, and causal factors in forecasts. The tool also provides detailed API reference for seamless integration into existing workflows.

ASK BOSCO® is an AI reporting and forecasting platform designed for agencies and retailers. It helps users collect and analyze data to improve decision-making, budget planning, and forecasting accuracy. The platform offers features such as AI reporting, competitor benchmarking, AI budget planning, and data integrations to streamline marketing processes and enhance performance. Trusted by leading brands and agencies, ASK BOSCO® provides personalized insights and recommendations to optimize media spend and drive revenue growth.

Hook is an AI-powered platform designed to help businesses grow their revenue by accurately predicting high-value customers, reducing churn, increasing expansion revenue, and actively managing accounts. The platform uses AI to analyze usage patterns and third-party data to prioritize customers for revenue growth and upsells. With a focus on data-driven decision-making, Hook empowers revenue teams to make informed choices and drive business growth.

Meyka is an AI-powered stock research tool that provides users with real-time stock data and analysis. Users can explore financial health, social sentiment analysis, earnings reports, comparison of financial statements, stock market news, DCF value, stock price forecasting, and recent grades for various stocks. The tool aims to assist users in making informed investment decisions by leveraging AI technology to analyze and predict stock market trends.

RELEX Solutions is a market-leading supply chain and retail planning platform that leverages artificial intelligence to revolutionize supply chains. The platform offers end-to-end inventory planning, production scheduling, demand forecasting, merchandising, assortment planning, price optimization, promotion planning, and more. RELEX enables retailers and consumer goods companies to align their supply chain and retail operations with actual demand, driving profitability through increased sales and reduced costs while minimizing waste. The platform caters to various industries such as retail, convenience, electronics, grocery, health, beauty, pharmaceutical, and more, providing tailored solutions for each sector.

Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

A catalogue and categorization of AI-based weather forecasting models. This page provides a catalogue and categorization of AI-based weather forecasting models to enable discovery and comparison of different available model options. The weather models are categorized based on metadata found in the JSON schema specification. The table includes information such as the name of the weather model, the organization that developed it, operational data availability, open-source status, and links for further details.

The Microsoft AI for Earth program hosts geospatial data on Azure that is important to environmental sustainability and Earth science. This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth. It also serves as a "staging ground" for the Planetary Computer Data Catalog.

Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of Large (Language) Models and Foundation Models for Temporal Data, including Time Series, Spatio-temporal, and Event Data. The repository aims to summarize recent advances in Large Models and Foundation Models for Time Series and Spatio-Temporal Data with resources such as papers, code, and data. It covers various applications like General Time Series Analysis, Transportation, Finance, Healthcare, Event Analysis, Climate, Video Data, and more. The repository also includes related resources, surveys, and papers on Large Language Models, Foundation Models, and their applications in AIOps.

The 'ai-dev-2024-ml-workshop' repository contains materials for the Deploy and Monitor ML Pipelines workshop at the AI_dev 2024 conference in Paris, focusing on deployment designs of machine learning pipelines using open-source applications and free-tier tools. It demonstrates automating data refresh and forecasting using GitHub Actions and Docker, monitoring with MLflow and YData Profiling, and setting up a monitoring dashboard with Quarto doc on GitHub Pages.

This repository contains custom recipes for H2O Driverless AI, which is an Automatic Machine Learning platform for the Enterprise. Custom recipes are Python code snippets that can be uploaded into Driverless AI at runtime to automate feature engineering, model building, visualization, and interpretability. Users can gain control over the optimization choices made by Driverless AI by providing their own custom recipes. The repository includes recipes for various tasks such as data manipulation, data preprocessing, feature selection, data augmentation, model building, scoring, and more. Best practices for creating and using recipes are also provided, including security considerations, performance tips, and safety measures.

WeatherGFT is a physics-AI hybrid model designed to generalize weather forecasts to finer-grained temporal scales beyond the training dataset. It incorporates physical partial differential equations (PDEs) into neural networks to simulate fine-grained physical evolution and correct biases. The model achieves state-of-the-art performance in forecasting tasks at different time scales, from nowcasting to medium-range forecasts, by utilizing a lead time-aware training framework and a carefully designed PDE kernel. WeatherGFT bridges the gap between nowcast and medium-range forecast by extending forecasting abilities to predict accurately at a 30-minute time scale.

Nixtla is a production-ready generative pretrained transformer for time series forecasting and anomaly detection. It can accurately predict various domains such as retail, electricity, finance, and IoT with just a few lines of code. TimeGPT introduces a paradigm shift with its standout performance, efficiency, and simplicity, making it accessible even to users with minimal coding experience. The model is based on self-attention and is independently trained on a vast time series dataset to minimize forecasting error. It offers features like zero-shot inference, fine-tuning, API access, adding exogenous variables, multiple series forecasting, custom loss function, cross-validation, prediction intervals, and handling irregular timestamps.

LLMsForTimeSeries is a repository that questions the usefulness of language models in time series forecasting. The work shows that simple baselines outperform most language model-based time series forecasting models. It includes ablation studies on LLM-based TSF methods and introduces the PAttn method, showcasing the performance of patching and attention structures in forecasting. The repository provides datasets, setup instructions, and scripts for running ablations on different datasets.

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.

Flyte is an open-source orchestrator that facilitates building production-grade data and ML pipelines. It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. With Flyte, user teams can construct pipelines using the Python SDK, and seamlessly deploy them on both cloud and on-premises environments, enabling distributed processing and efficient resource utilization.

FootBallPrediction (FBP) is a software project that utilizes big data and machine learning to predict the outcome of football matches based on odds from gambling companies. The software has achieved an accuracy rate of over 80% in predicting match results. The current version, 22.0, successfully predicted eight out of nine matches from major football leagues. The project has a community of over 60 members who benefit from the predicted results. The author is seeking collaboration to further enhance the project and welcomes interested individuals to join. AI-FBP is a subscription service that provides daily football game predictions.

DeepSparkHub is a repository that curates hundreds of application algorithms and models covering various fields in AI and general computing. It supports mainstream intelligent computing scenarios in markets such as smart cities, digital individuals, healthcare, education, communication, energy, and more. The repository provides a wide range of models for tasks such as computer vision, face detection, face recognition, instance segmentation, image generation, knowledge distillation, network pruning, object detection, 3D object detection, OCR, pose estimation, self-supervised learning, semantic segmentation, super resolution, tracking, traffic forecast, GNN, HPC, methodology, multimodal, NLP, recommendation, reinforcement learning, speech recognition, speech synthesis, and 3D reconstruction.

TaskWeaver is a code-first agent framework designed for planning and executing data analytics tasks. It interprets user requests through code snippets, coordinates various plugins to execute tasks in a stateful manner, and preserves both chat history and code execution history. It supports rich data structures, customized algorithms, domain-specific knowledge incorporation, stateful execution, code verification, easy debugging, security considerations, and easy extension. TaskWeaver is easy to use with CLI and WebUI support, and it can be integrated as a library. It offers detailed documentation, demo examples, and citation guidelines.

Lightning Lab is a public template for artificial intelligence and machine learning research projects using Lightning AI's PyTorch Lightning. It provides a structured project layout with modules for command line interface, experiment utilities, Lightning Module and Trainer, data acquisition and preprocessing, model serving APIs, project configurations, training checkpoints, technical documentation, logs, notebooks for data analysis, requirements management, testing, and packaging. The template simplifies the setup of deep learning projects and offers extras for different domains like vision, text, audio, reinforcement learning, and forecasting.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

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.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

The `ai-models` command is a tool used to run AI-based weather forecasting models. It provides functionalities to install, run, and manage different AI models for weather forecasting. Users can easily install and run various models, customize model settings, download assets, and manage input data from different sources such as ECMWF, CDS, and GRIB files. The tool is designed to optimize performance by running on GPUs and provides options for better organization of assets and output files. It offers a range of command line options for users to interact with the models and customize their forecasting tasks.

Advanced predictive analysis tool

A chatbot expert in business data analysis and optimization.

Excel spreadsheet data analysis expert

Friendly Excel and Google Sheets guide, making complex concepts easy.

Expert in ads incrementality and campaign will help you interpret data, forecasting and share you testing frameworks using advanced Python libraries

Analytical helper for identifying data patterns and trends

Expert economist with access to real-time data.

Guides financial strategy through data analysis and forecasting.

Generate synthetic timeseries data

Gann Theory expert with data analysis and user input processing.

Your compass in India's Economic Terrain. Expert on India's economic landscape, integrating latest insights and data. Disclaimer: https://www.elixirequities.com/disclaimers

Data analysis and insight tool for SMEs.

Enhances financial decision-making by analyzing, interpreting and reporting financial data.

Expert in epidemiology, modeling disease spread and analyzing public health data.

Fun Weather forecaster.

Revolutionizing Sales Automation & Data Mastery

A guide with current 'The Pathless Path' sales data

BuffettMungerDuan Finance AI' revolutionizes financial analysis, blending Buffett, Munger, and Duan's insights. Advanced algorithms and a vast database empower precise market forecasts and strategies, essential for investors and financial pros

专业预测师，基于用户数据提供预测反馈。

Expert on government spending, budgets, and fiscal policy.