Best AI tools for< Data Analysis >

Zeus Notebook is an AI code assistant designed by Ying Hang Seah. It allows users to run a Python notebook entirely on their browser. Users can enter their OpenAI API key to enable chat functionality. The application is a helpful tool for developers and programmers to get assistance with coding tasks and projects.

HireLakeAI is an AI-powered platform that helps businesses with their hiring process. It uses AI to automate tasks such as resume screening, candidate matching, and interview scheduling. HireLakeAI also provides insights into candidate data, such as their skills, experience, and personality. This information can help businesses make better hiring decisions and improve their overall hiring process.

Mito is a low-code data app infrastructure that allows users to edit spreadsheets and automatically generate Python code. It is designed to help analysts automate their repetitive Excel work and take automation into their own hands. Mito is a Jupyter extension and Streamlit component, so users don't need to set up any new infrastructure. It is easy to get started with Mito, simply install it using pip and start using it in Jupyter or Streamlit.

DataCamp is an online learning platform that offers courses in data science, AI, and machine learning. The platform provides interactive exercises, short videos, and hands-on projects to help learners develop the skills they need to succeed in the field. DataCamp also offers a variety of resources for businesses, including team training, custom content development, and data science consulting.

OSO is an AI-powered tool suite that offers a range of capabilities to enhance productivity and streamline tasks. It includes an AI search engine that provides comprehensive summaries of search queries, an uncensored AI chat that allows for unrestricted discussions and content generation, and an AI image generation tool that enables the creation of visuals for various purposes. OSO integrates with over 7,000 applications and offers a range of features such as workflow automation, web summaries, and sentiment analysis.

Hex is a collaborative data workspace that provides a variety of tools for working with data, including queries, notebooks, reports, data apps, and AI. It is designed to be easy to use for people of all technical skill levels, and it integrates with a variety of other tools and services. Hex is a powerful tool for data exploration, analysis, and visualization.

Hyperscience is a leading enterprise AI platform that provides hyperautomation solutions for businesses. Its platform enables organizations to automate complex business processes with high accuracy and efficiency. Hyperscience offers a range of solutions across various industries and processes, leveraging technologies such as intelligent document processing, machine learning, and natural language processing. The platform is designed to help businesses transform their operations, improve decision-making, and gain a competitive advantage.

PwC is a global network of professional services firms that provides assurance, tax, and consulting services to businesses and individuals. The company has a strong focus on artificial intelligence (AI) and its potential to transform the way businesses operate. PwC's AI-powered solutions help clients improve efficiency, reduce costs, and make better decisions.

XtalPi is a world-leading technology company driven by artificial intelligence (AI) and robotics to innovate in the fields of life sciences and new materials. Founded in 2015 at the Massachusetts Institute of Technology (MIT), the company is committed to realizing digital and intelligent innovation in the fields of life sciences and new materials. Based on cutting-edge technologies and capabilities such as quantum physics, artificial intelligence, cloud computing, and large-scale experimental robot clusters, the company provides innovative technologies, services, and products for global industries such as biomedicine, chemicals, new energy, and new materials.

Sacred is a tool to configure, organize, log and reproduce computational experiments. It is designed to introduce only minimal overhead, while encouraging modularity and configurability of experiments. The ability to conveniently make experiments configurable is at the heart of Sacred. If the parameters of an experiment are exposed in this way, it will help you to: keep track of all the parameters of your experiment easily run your experiment for different settings save configurations for individual runs in files or a database reproduce your results In Sacred we achieve this through the following main mechanisms: Config Scopes are functions with a @ex.config decorator, that turn all local variables into configuration entries. This helps to set up your configuration really easily. Those entries can then be used in captured functions via dependency injection. That way the system takes care of passing parameters around for you, which makes using your config values really easy. The command-line interface can be used to change the parameters, which makes it really easy to run your experiment with modified parameters. Observers log every information about your experiment and the configuration you used, and saves them for example to a Database. This helps to keep track of all your experiments. Automatic seeding helps controlling the randomness in your experiments, such that they stay reproducible.

Databricks is a data and AI company that provides a unified platform for data, analytics, and AI. The platform includes a variety of tools and services for data management, data warehousing, real-time analytics, data engineering, data science, and AI development. Databricks also offers a variety of integrations with other tools and services, such as ETL tools, data ingestion tools, business intelligence tools, AI tools, and governance tools.

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.

Posit is an open-source data science company that provides a suite of tools and services for data scientists. Its products include the RStudio IDE, Shiny, and Posit Connect. Posit also offers cloud-based solutions and enterprise support. The company's mission is to make data science accessible to everyone, regardless of their economic means or technical expertise.

Tabula is a visual data analytics tool that uses AI to help businesses get insights from their data. It is easy to use and can be used by anyone, regardless of their technical expertise. Tabula can be used to access and unify data from a variety of sources, standardize and blend datasets, add custom metrics, build stunning reports, and automate repetitive tasks. Tabula is integrated with a variety of data sources and platforms, making it easy to get started.

Amperity is a leading AI enterprise customer data platform (CDP) for consumer brands. It provides a data foundation prepared by AI, allowing anyone to become a data scientist with Generative AI. Amperity's AI-powered capabilities include Explore, Assist, Stitch, and Predict.

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.

ScreenAI is a powerful macOS application that leverages advanced multimodal AI to enhance productivity. By simply taking a screenshot, users can automate tasks such as scheduling, content explanation, and chat responses. The application seamlessly integrates with Apple's native apps, providing an immersive and efficient user experience. With a focus on privacy and data security, ScreenAI ensures that all data stays local and partners only with trusted AI service providers.

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.

GPT Personalize is a platform offering free custom GPTs designed to enhance productivity in various domains such as education, tech support, and more. Users can access a range of custom GPTs with a ChatGPT Plus or Enterprise subscription, making tasks easier and learning more fun. The platform also provides expert guides on integrating knowledge into GPTs, mastering DNS management, and developing innovative actions for GPT models. GPT Personalize aims to optimize tasks and accelerate learning through the power of generative AI.

AI-Driven Research Assistant is an advanced AI-powered system utilizing specialized agents for data analysis, visualization, and report generation. It integrates LangChain, OpenAI's GPT models, and LangGraph for complex research processes. Key features include hypothesis generation, data processing, web search, code generation, and report writing. The system's unique Note Taker agent maintains project state, reducing overhead and improving context retention. System requirements include Python 3.10+ and Jupyter Notebook environment. Installation involves cloning the repository, setting up a Conda virtual environment, installing dependencies, and configuring environment variables. Usage instructions include setting data, running Jupyter Notebook, customizing research tasks, and viewing results. Main components include agents for hypothesis generation, process supervision, visualization, code writing, search, report writing, quality review, and note-taking. Workflow involves hypothesis generation, processing, quality review, and revision. Customization is possible by modifying agent creation and workflow definition. Current issues include OpenAI errors, NoteTaker efficiency, runtime optimization, and refiner improvement. Contributions via pull requests are welcome under the MIT License.

A curated list of data science & AI guided projects to start building your portfolio. The repository contains guided projects covering various topics such as large language models, time series analysis, computer vision, natural language processing (NLP), and data science. Each project provides detailed instructions on how to implement specific tasks using different tools and technologies.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

Data Formulator is an AI-powered tool developed by Microsoft Research to help data analysts create rich visualizations iteratively. It combines user interface interactions with natural language inputs to simplify the process of describing chart designs while delegating data transformation to AI. Users can utilize features like blended UI and NL inputs, data threads for history navigation, and code inspection to create impressive visualizations. The tool supports local installation for customization and Codespaces for quick setup. Developers can build new data analysis tools on top of Data Formulator, and research papers are available for further reading.

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.

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.

DataLine is an AI-driven data analysis and visualization tool designed for technical and non-technical users to explore data quickly. It offers privacy-focused data storage on the user's device, supports various data sources, generates charts, executes queries, and facilitates report building. The tool aims to speed up data analysis tasks for businesses and individuals by providing a user-friendly interface and natural language querying capabilities.

Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates tasks such as data cleaning, preprocessing, and complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless. It aims to expedite the data analysis process, making it accessible to all, regardless of their expertise in data analysis. The tool is built to empower users to process data and achieve high-quality visualizations with unparalleled efficiency, and to execute high-performance modeling with the best strategies. Future enhancements include Natural Language Processing (NLP), neural networks, and object detection utilizing YOLO, broadening its capabilities to meet diverse data analysis needs.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

LLMs4TS is a repository focused on the application of cutting-edge AI technologies for time-series analysis. It covers advanced topics such as self-supervised learning, Graph Neural Networks for Time Series, Large Language Models for Time Series, Diffusion models, Mixture-of-Experts architectures, and Mamba models. The resources in this repository span various domains like healthcare, finance, and traffic, offering tutorials, courses, and workshops from prestigious conferences. Whether you're a professional, data scientist, or researcher, the tools and techniques in this repository can enhance your time-series data analysis capabilities.

DeepBI is an AI-native data analysis platform that leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions.

Chat2DB is an AI-driven data development and analysis platform that enables users to communicate with databases using natural language. It supports a wide range of databases, including MySQL, PostgreSQL, Oracle, SQLServer, SQLite, MariaDB, ClickHouse, DM, Presto, DB2, OceanBase, Hive, KingBase, MongoDB, Redis, and Snowflake. Chat2DB provides a user-friendly interface that allows users to query databases, generate reports, and explore data using natural language commands. It also offers a variety of features to help users improve their productivity, such as auto-completion, syntax highlighting, and error checking.

DataAgent is a multi-agent system for data analysis, capable of understanding data development and data analysis requirements, understanding data, and generating SQL and Python code for tasks such as data query, data visualization, and machine learning.

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.

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).

airda(Air Data Agent) is a multi-agent system for data analysis, which can understand data development and data analysis requirements, understand data, and generate SQL and Python code for data query, data visualization, machine learning and other tasks.

Generative AI with LangChain is a code repository for building large language model (LLM) apps with Python, ChatGPT, and other LLMs. The repository provides code examples, instructions, and configurations for creating generative AI applications using the LangChain framework. It covers topics such as setting up the development environment, installing dependencies with Conda or Pip, using Docker for environment setup, and setting API keys securely. The repository also emphasizes stability, code updates, and user engagement through issue reporting and feedback. It aims to empower users to leverage generative AI technologies for tasks like building chatbots, question-answering systems, software development aids, and data analysis applications.

Ryoma is an AI Powered Data Agent framework that offers a comprehensive solution for data analysis, engineering, and visualization. It leverages cutting-edge technologies like Langchain, Reflex, Apache Arrow, Jupyter Ai Magics, Amundsen, Ibis, and Feast to provide seamless integration of language models, build interactive web applications, handle in-memory data efficiently, work with AI models, and manage machine learning features in production. Ryoma also supports various data sources like Snowflake, Sqlite, BigQuery, Postgres, MySQL, and different engines like Apache Spark and Apache Flink. The tool enables users to connect to databases, run SQL queries, and interact with data and AI models through a user-friendly UI called Ryoma Lab.

LitLytics is an affordable analytics platform leveraging LLMs for automated data analysis. It simplifies analytics for teams without data scientists, generates custom pipelines, and allows customization. Cost-efficient with low data processing costs. Scalable and flexible, works with CSV, PDF, and plain text data formats.

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.

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Does some data analysis for you

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it helps me analyze serp results and data from certain websites in order to create an outline for the writer

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Data trend analysis expert in cannabis, also skilled in image and data analysis, document generation, and web search.

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Expert in diverse environmental data analysis and reporting.

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Casual and approachable Python data analysis helper.