Best AI tools for< Perform Data Analysis >

Latitude is an open-source framework for building interactive data apps using code. It provides a workspace for data analysts to streamline their workflow, connect to various data sources, perform data transformations, create visualizations, and collaborate with others. Latitude aims to simplify the data analysis process by offering features such as data snapshots, a data profiler, a built-in AI assistant, and tight integration with dbt.

Deepsheet is a cloud-based spreadsheet application that uses artificial intelligence to help users analyze and visualize data. It offers a variety of features, including the ability to import data from a variety of sources, create charts and graphs, and perform data analysis. Deepsheet is designed to be easy to use, even for users with no prior experience with spreadsheets.

Aitodata.com is an AI-powered data analysis tool designed to help users analyze and visualize data efficiently. The platform offers a user-friendly interface that allows users to upload datasets, perform various data analysis tasks, and generate insightful visualizations. With advanced AI algorithms, aitodata.com simplifies the data analysis process and provides valuable insights to users across different industries. Whether you are a data scientist, business analyst, or student, aitodata.com can assist you in making data-driven decisions and uncovering hidden patterns in your data.

MarkovML is an AI application that empowers enterprises to transform knowledge work with AI. It offers a no-code platform to create custom workflows, build GenAI applications, and perform automated exploratory data analysis. The application provides AI-driven solutions for EdTech, recruiting, and finance operations. Users can access insights, trends, and machine learning resources through the blog and share data insights with peers. MarkovML ensures data security, traceability, and encryption, and offers integrations with various data sources for unified access and reuse.

Vizly is an AI-powered data analysis tool that empowers users to make the most of their data. It allows users to chat with their data, visualize insights, and perform complex analysis. Vizly supports various file formats like CSV, Excel, and JSON, making it versatile for different data sources. The tool is free to use for up to 10 messages per month and offers a student discount of 50%. Vizly is suitable for individuals, students, academics, and organizations looking to gain actionable insights from their data.

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.

Julius is an AI-powered tool that helps users analyze data and files. It can perform various tasks such as generating visualizations, answering data questions, and performing statistical modeling. Julius is designed to save users time and effort by automating complex data analysis tasks.

Websim.ai is an advanced AI tool designed to provide users with a powerful platform for simulating and analyzing web data. With cutting-edge algorithms and machine learning capabilities, Websim.ai offers a comprehensive suite of tools for web data analysis, visualization, and prediction. Users can easily upload their data sets, perform complex analyses, and generate insightful reports to gain valuable insights into their web performance and user behavior. Whether you are a data scientist, marketer, or business owner, Websim.ai empowers you to make informed decisions and optimize your online presence.

Cohesive is an AI tool designed to provide outsourced analysts and assistants for businesses. It enables users to prospect at scale, perform outbound activities with AI enrichment and web scraping directly within Google Sheets. The tool is Google Sheets native, allowing users to enrich and scrape the web without the need to import data into a separate platform. Cohesive also leverages AI for bulk data analysis, personalization generation, web scraping, and email finding/validation. It offers free usage with the option to join the Cohesive Slack community for additional support.

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and high-level mathematical functions to perform operations on these arrays. It is the fundamental package for scientific computing with Python and is used in a wide range of applications, including data science, machine learning, and image processing. NumPy is open source and distributed under a liberal BSD license, and is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.

Alteryx offers a leading AI Platform for Enterprise Analytics that delivers actionable insights by automating analytics. The platform combines the power of data preparation, analytics, and machine learning to help businesses make better decisions faster. With Alteryx, businesses can connect to a wide variety of data sources, prepare and clean data, perform advanced analytics, and build and deploy machine learning models. The platform is designed to be easy to use, even for non-technical users, and it can be deployed on-premises or in the cloud.

Luminal is a powerful AI copilot that helps users clean, transform, and analyze spreadsheets 10x faster. It offers fast and efficient data analysis capabilities, enabling users to perform complex operations and run AI-enabled tasks using natural language. With Luminal, users can visualize data, ask complex questions, and clean and format spreadsheets effortlessly. The application supports multiple languages, provides secure data hosting with encryption, and offers simple pricing that scales with user needs.

SheetMagic is an AI-powered tool that allows users to perform various tasks within Google Sheets, including generating AI content, web scraping, data analysis, and data preparation. It integrates with ChatGPT, allowing users to access advanced AI capabilities without coding or hiring developers. SheetMagic is designed to enhance productivity and streamline workflows for individuals and teams.

MimicPC is a web-based platform that allows users to run various AI applications directly in their browser without the need for installation. Users can access a wide range of AI tools and applications seamlessly, making it convenient for both professionals and enthusiasts to leverage the power of artificial intelligence. With MimicPC, users can perform tasks such as image recognition, natural language processing, and data analysis with ease.

Mediar is a generative AI tool that helps users maximize the number of operations they can perform. It is designed to be easy to use and can be used for a variety of tasks, including content creation, data analysis, and software development.

Sintra is an AI-powered platform that offers a range of digital assistants to help with various tasks, from customer support and SEO to email marketing and data analysis. The platform aims to make work more enjoyable by providing efficient and effective AI helpers that can perform tasks on demand. Sintra's digital assistants are designed to streamline processes and improve productivity for individuals and businesses.

Spreadsheet Daddy is an AI-powered add-on for Google Sheets that enables users to automate tasks, generate content, extract data, and perform various other functions using advanced AI models like GPT-4 and GPT-4-32k. It seamlessly integrates with Google Sheets, allowing users to leverage the power of AI within their spreadsheets. With its user-friendly interface and diverse range of features, Spreadsheet Daddy empowers businesses and individuals to enhance their productivity and efficiency.

KYP.ai is a productivity intelligence platform that offers a 360° view of organizations across people, process, and technology dimensions. It provides instant productivity intelligence, end-to-end process optimization, holistic productivity insights, ROI-driven automation, and unparalleled scalability. The platform helps in live visibility, immediate impact, hybrid workplace management, technology landscape rationalization, and AI-powered aggregation and analysis. KYP.ai focuses on workforce enablement, no integration hassles, no-code configuration, and secure, privacy-compliant data processing.

Anthropic is a research and deployment company founded in 2021 by former OpenAI researchers Dario Amodei, Daniela Amodei, and Geoffrey Irving. The company is developing large language models, including Claude, a multimodal AI model that can perform a variety of language-related tasks, such as answering questions, generating text, and translating languages.

xPDF AI by PDFChat is a personal AI assistant designed for PDF files. It offers advanced features to analyze tables, figures, and text from PDF documents, providing users with instant answers and insights. The AI assistant uses a chat interface for effortless interaction and is capable of summarizing PDF files, retrieving relevant figures, processing tables intelligently, and performing accurate calculations. Users can also benefit from voice chat, advanced search tools, performance analytics, report generation, and document assistance. With over 10,000 users trusting the platform, PDFChat aims to revolutionize document analysis and enhance productivity.

LAMBDA is a code-free multi-agent data analysis system that utilizes large models to address data analysis challenges in complex data-driven applications. It allows users to perform complex data analysis tasks through human language instruction, seamlessly generate and debug code using two key agent roles, integrate external models and algorithms, and automatically generate reports. The system has demonstrated strong performance on various machine learning datasets, enhancing data science practice by integrating human and artificial intelligence.

Vivaria is a web application tool designed for running evaluations and conducting agent elicitation research. Users can interact with Vivaria using a web UI and a command-line interface. It allows users to start task environments based on METR Task Standard definitions, run AI agents, perform agent elicitation research, view API requests and responses, add tags and comments to runs, store results in a PostgreSQL database, sync data to Airtable, test prompts against LLMs, and authenticate using Auth0.

Phidata is a framework for building AI Assistants with memory, knowledge, and tools. It enables LLMs to have long-term conversations by storing chat history in a database, provides them with business context by storing information in a vector database, and enables them to take actions like pulling data from an API, sending emails, or querying a database. Memory and knowledge make LLMs smarter, while tools make them autonomous.

GPTMe is a tool that allows users to interact with an LLM assistant directly in their terminal in a chat-style interface. The tool provides features for the assistant to run shell commands, execute code, read/write files, and more, making it suitable for various development and terminal-based tasks. It serves as a local alternative to ChatGPT's 'Code Interpreter,' offering flexibility and privacy when using a local model. GPTMe supports code execution, file manipulation, context passing, self-correction, and works with various AI models like GPT-4. It also includes a GitHub Bot for requesting changes and operates entirely in GitHub Actions. In progress features include handling long contexts intelligently, a web UI and API for conversations, web and desktop vision, and a tree-based conversation structure.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

This project enables you to fetch liked tweets from Twitter (using Selenium), save it to JSON and Excel files, and perform initial data analysis and image captions. This is part of the initial steps for a larger personal project involving Large Language Models (LLMs).

cassIO is a framework-agnostic Python library that seamlessly integrates Apache Cassandra with ML/LLM/genAI workloads. It provides an easy-to-use interface for developers to connect their Cassandra databases to machine learning models, allowing them to perform complex data analysis and AI-powered tasks directly on their Cassandra data. cassIO is designed to be flexible and extensible, making it suitable for a wide range of use cases, from data exploration and visualization to predictive modeling and natural language processing.

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.

OAD is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for exploring datasets, generating insights, and creating interactive visualizations. With OAD, users can easily import data from various sources, clean and preprocess data, perform statistical analysis, and create customizable visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, OAD can help you streamline your data analysis workflow and uncover valuable insights from your data.

DataFrame is a C++ analytical library designed for data analysis similar to libraries in Python and R. It allows you to slice, join, merge, group-by, and perform various statistical, summarization, financial, and ML algorithms on your data. DataFrame also includes a large collection of analytical algorithms in form of visitors, ranging from basic stats to more involved analysis. You can easily add your own algorithms as well. DataFrame employs extensive multithreading in almost all its APIs, making it suitable for analyzing large datasets. Key principles followed in the library include supporting any type without needing new code, avoiding pointer chasing, having all column data in contiguous memory space, minimizing space usage, avoiding data copying, using multi-threading judiciously, and not protecting the user against garbage in, garbage out.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

Awesome AI & Data GitHub-Repos is a curated list of essential GitHub repositories covering the AI & ML landscape. It includes resources for Natural Language Processing, Large Language Models, Computer Vision, Data Science, Machine Learning, MLOps, Data Engineering, SQL & Database, and Statistics. The repository aims to provide a comprehensive collection of projects and resources for individuals studying or working in the field of AI and data science.

BambooAI is a lightweight library utilizing Large Language Models (LLMs) to provide natural language interaction capabilities, much like a research and data analysis assistant enabling conversation with your data. You can either provide your own data sets, or allow the library to locate and fetch data for you. It supports Internet searches and external API interactions.

Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.

InternLM is a powerful language model series with features such as 200K context window for long-context tasks, outstanding comprehensive performance in reasoning, math, code, chat experience, instruction following, and creative writing, code interpreter & data analysis capabilities, and stronger tool utilization capabilities. It offers models in sizes of 7B and 20B, suitable for research and complex scenarios. The models are recommended for various applications and exhibit better performance than previous generations. InternLM models may match or surpass other open-source models like ChatGPT. The tool has been evaluated on various datasets and has shown superior performance in multiple tasks. It requires Python >= 3.8, PyTorch >= 1.12.0, and Transformers >= 4.34 for usage. InternLM can be used for tasks like chat, agent applications, fine-tuning, deployment, and long-context inference.

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.

FiftyOne is an open-source tool designed for building high-quality datasets and computer vision models. It supercharges machine learning workflows by enabling users to visualize datasets, interpret models faster, and improve efficiency. With FiftyOne, users can explore scenarios, identify failure modes, visualize complex labels, evaluate models, find annotation mistakes, and much more. The tool aims to streamline the process of improving machine learning models by providing a comprehensive set of features for data analysis and model interpretation.

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.

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