Best AI tools for< Data Scientist >

The Association of Data Scientists (ADaSci) is a global professional body of AI professionals that accredits and elevates professionals with recognized certifications and transformative corporate training. They offer memberships for individuals and corporations interested in the AI field, as well as accreditations like Chartered Data Scientist (CDS) and Certified Generative AI Engineer. The organization provides continuous learning opportunities through courses and corporate training programs on topics such as generative AI and knowledge graph solutions. ADaSci aims to shape the future of AI talent by advancing expertise and achieving global recognition as certified professionals.

Kaggle is a platform for data science and machine learning enthusiasts to collaborate, learn, and compete. It offers a wide range of datasets, competitions, and notebooks for users to practice and showcase their skills. With a vibrant community of data scientists and experts, Kaggle provides a valuable resource for both beginners and professionals to enhance their knowledge and expertise in the field of data science and machine learning.

WiseData is an AI Assistant for Python Data Analytics designed to help Data Analysts and Data Scientists be 2X more productive. It offers features like data transformation with natural language, data visualization with natural language, and data transformation with SQL. WiseData ensures privacy by not sending analyzed data to its server and protects transmitted prompts and suggestions through encryption. It is a valuable tool for simplifying complex data analytics tasks and enhancing productivity.

Towards Data Science is a Medium publication dedicated to sharing concepts, ideas, and codes in the field of data science. It provides a platform for data scientists, researchers, and practitioners to connect, learn, and contribute to the advancement of the field.

Domino Data Lab is an enterprise AI platform that enables data scientists and IT leaders to build, deploy, and manage AI models at scale. It provides a unified platform for accessing data, tools, compute, models, and projects across any environment. Domino also fosters collaboration, establishes best practices, and tracks models in production to accelerate and scale AI while ensuring governance and reducing costs.

Open Data Science (ODS) is a community website offering a platform for data science enthusiasts to engage in tracks, competitions, hacks, tasks, events, and projects. The website serves as a hub for job opportunities and provides a space for privacy policy, service agreements, and public offers. ODS.AI, established in 2015, focuses on various data science topics such as machine learning, computer vision, natural language processing, and more. The platform hosts online and offline events, conferences, and educational courses to foster learning and networking within the data science community.

Domino Data Lab is an enterprise AI platform that enables users to build, deploy, and manage AI models across any environment. It fosters collaboration, establishes best practices, and ensures governance while reducing costs. The platform provides access to a broad ecosystem of open source and commercial tools, and infrastructure, allowing users to accelerate and scale AI impact. Domino serves as a central hub for AI operations and knowledge, offering integrated workflows, automation, and hybrid multicloud capabilities. It helps users optimize compute utilization, enforce compliance, and centralize knowledge across teams.

The Research Center Trustworthy Data Science and Security is a hub for interdisciplinary research focusing on building trust in artificial intelligence, machine learning, and cyber security. The center aims to develop trustworthy intelligent systems through research in trustworthy data analytics, explainable machine learning, and privacy-aware algorithms. By addressing the intersection of technological progress and social acceptance, the center seeks to enable private citizens to understand and trust technology in safety-critical applications.

Macgence is an AI training data services platform that offers high-quality off-the-shelf structured training data for organizations to build effective AI systems at scale. They provide services such as custom data sourcing, data annotation, data validation, content moderation, and localization. Macgence combines global linguistic, cultural, and technological expertise to create high-quality datasets for AI models, enabling faster time-to-market across the entire model value chain. With more than 5 years of experience, they support and scale AI initiatives of leading global innovators by designing custom data collection programs. Macgence specializes in handling AI training data for text, speech, image, and video data, offering cognitive annotation services to unlock the potential of unstructured textual data.

Compact Data Science is a data science platform that provides a comprehensive set of tools and resources for data scientists and analysts. The platform includes a variety of features such as data preparation, data visualization, machine learning, and predictive analytics. Compact Data Science is designed to be easy to use and accessible to users of all skill levels.

Dot Group is an AI-powered data advisory and solutions platform that specializes in effective data management. They offer services to help businesses maximize the potential of their data estate, turning complex challenges into profitable opportunities using AI technologies. With a focus on data strategy, data engineering, and data transport, Dot Group provides innovative solutions to drive better profitability for their clients.

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.

Humbi AI is an AI-powered platform offering actuarial services for healthcare organizations, health plans, provider organizations, and drug manufacturers. The platform combines data science and actuarial expertise to provide competitive intelligence analytics, helping clients identify opportunities and manage risks effectively. Humbi AI offers a range of services from data management to actuarial design, incorporating knowledge from various fields such as medical science and technology. The platform includes tools for Medicare Advantage strategy building, provider performance comparison, pharmacy management, and access to medical and pharmacy data for millions of members.

The website page text discusses the latest advancements in AI technology, specifically focusing on the introduction of AI assistants and capabilities by various companies. It highlights the use of Large Language Models (LLMs) and generative AI to enhance customer service experiences, improve operational efficiency, and drive innovation across industries. The text showcases how AI avatars powered by NVIDIA technology are revolutionizing customer interactions and employee service experiences. It also mentions the collaboration between ServiceNow and NVIDIA to develop AI avatars for Now Assist, demonstrating the potential for more engaging and personalized communication through digital characters. Additionally, the text features the launch of Orchestrator LLM by Yellow.ai, an agent model that enables contextually aware and human-like customer conversations without the need for training, leading to increased customer satisfaction and operational efficiency.

Data Science Dojo is a globally recognized e-learning platform that offers programs in data science, data analytics, machine learning, and more. They provide comprehensive and hands-on training in various formats such as in-person, virtual instructor-led, and self-paced training. The focus is on helping students develop a think-business-first mindset to apply their data science skills effectively in real-world scenarios. With over 2500 enterprises trained, Data Science Dojo aims to make data science accessible to everyone.

The Data & Trust Alliance is a group of industry-leading enterprises focusing on the responsible use of data and intelligent systems. They develop practices to enhance trust in data and AI models, ensuring transparency and reliability in the deployment processes. The alliance works on projects like Data Provenance Standards and Assessing third-party model trustworthiness to promote innovation and trust in AI applications. Through technology and innovation adoption, they aim to leverage expertise and influence for practical solutions and broad adoption across industries.

One Data is an AI-powered data product builder that offers a comprehensive solution for building, managing, and sharing data products. It bridges the gap between IT and business by providing AI-powered workflows, lifecycle management, data quality assurance, and data governance features. The platform enables users to easily create, access, and share data products with automated processes and quality alerts. One Data is trusted by enterprises and aims to streamline data product management and accessibility through Data Mesh or Data Fabric approaches, enhancing efficiency in logistics and supply chains. The application is designed to accelerate business impact with reliable data products and support cost reduction initiatives with advanced analytics and collaboration for innovative business models.

What's The Big Data is an AI tool directory that helps users unleash their potential by providing a comprehensive source for AI tools, data, and ChatGPT. The platform is updated daily and caters to every need, offering a wide range of AI assistants across various categories. Users can easily find their perfect AI assistant with just a click, making it a valuable resource for those seeking AI solutions.

ThirdEye Data is a data and AI services & solutions provider that enables enterprises to improve operational efficiencies, increase production accuracies, and make informed business decisions by leveraging the latest Data & AI technologies. They offer services in data engineering, data science, generative AI, computer vision, NLP, and more. ThirdEye Data develops bespoke AI applications using the latest data science technologies to address real-world industry challenges and assists enterprises in leveraging generative AI models to develop custom applications. They also provide AI consulting services to explore potential opportunities for AI implementation. The company has a strong focus on customer success and has received positive reviews and awards for their expertise in AI, ML, and big data solutions.

Rapid AI DAta Yields (RAIDAY) is a platform that provides AI tools, data products, and educational resources to help businesses and individuals leverage the power of artificial intelligence. RAIDAY's mission is to democratize and streamline the creation of simple yet powerful AI and data products for everyone, regardless of their technical expertise or resources. The platform offers a range of AI tools, including content generators, data analysis tools, and AI-powered chatbots. RAIDAY also provides a library of AI-generated content and data products that can be used to train AI models or to create new AI applications. In addition to its AI tools and data products, RAIDAY also offers a variety of educational resources, including tutorials, webinars, and blog posts, to help users learn about AI and how to use it effectively.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

Metaflow is a user-friendly library designed to assist scientists and engineers in developing and managing real-world data science projects. Initially created at Netflix, Metaflow aimed to enhance the productivity of data scientists working on diverse projects ranging from traditional statistics to cutting-edge deep learning. For further information, refer to Metaflow's website and documentation.

KitOps is a packaging and versioning system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using. KitOps simplifies the handoffs between data scientists, application developers, and SREs working with LLMs and other AI/ML models. KitOps' ModelKits are a standards-based package for models, their dependencies, configurations, and codebases. ModelKits are portable, reproducible, and work with the tools you already use.

CoML (formerly MLCopilot) is an interactive coding assistant for data scientists and machine learning developers, empowered on large language models. It offers an out-of-the-box interactive natural language programming interface for data mining and machine learning tasks, integration with Jupyter lab and Jupyter notebook, and a built-in large knowledge base of machine learning to enhance the ability to solve complex tasks. The tool is designed to assist users in coding tasks related to data analysis and machine learning using natural language commands within Jupyter environments.

Geoweaver is an in-browser software that enables users to easily compose and execute full-stack data processing workflows using online spatial data facilities, high-performance computation platforms, and open-source deep learning libraries. It provides server management, code repository, workflow orchestration software, and history recording capabilities. Users can run it from both local and remote machines. Geoweaver aims to make data processing workflows manageable for non-coder scientists and preserve model run history. It offers features like progress storage, organization, SSH connection to external servers, and a web UI with Python support.

This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

KWeaver is an open-source cognitive intelligence development framework that provides data scientists, application developers, and domain experts with the ability for rapid development, comprehensive openness, and high-performance knowledge network generation and cognitive intelligence large model framework. It offers features such as automated and visual knowledge graph construction, visualization and analysis of knowledge graph data, knowledge graph integration, knowledge graph resource management, large model prompt engineering and debugging, and visual configuration for large model access.

This repository provides a hands-on lab for learning about Neo4j and Google Cloud Vertex AI. It is intended for data scientists and data engineers to deploy Neo4j and Vertex AI in a Google Cloud account, work with real-world datasets, apply generative AI, build a chatbot over a knowledge graph, and use vector search and index functionality for semantic search. The lab focuses on analyzing quarterly filings of asset managers with $100m+ assets under management, exploring relationships using Neo4j Browser and Cypher query language, and discussing potential applications in capital markets such as algorithmic trading and securities master data management.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

ARTKIT is a Python framework developed by BCG X for automating prompt-based testing and evaluation of Gen AI applications. It allows users to develop automated end-to-end testing and evaluation pipelines for Gen AI systems, supporting multi-turn conversations and various testing scenarios like Q&A accuracy, brand values, equitability, safety, and security. The framework provides a simple API, asynchronous processing, caching, model agnostic support, end-to-end pipelines, multi-turn conversations, robust data flows, and visualizations. ARTKIT is designed for customization by data scientists and engineers to enhance human-in-the-loop testing and evaluation, emphasizing the importance of tailored testing for each Gen AI use case.

Generative AI on AWS by O'Reilly Media provides a comprehensive guide on leveraging generative AI models on the AWS platform. The book covers various topics such as generative AI use cases, prompt engineering, large-language models, fine-tuning techniques, optimization, deployment, and more. Authors Chris Fregly, Antje Barth, and Shelbee Eigenbrode offer insights into cutting-edge AI technologies and practical applications in the field. The book is a valuable resource for data scientists, AI enthusiasts, and professionals looking to explore generative AI capabilities on AWS.

Elyra is a set of AI-centric extensions to JupyterLab Notebooks that includes features like Visual Pipeline Editor, running notebooks/scripts as batch jobs, reusable code snippets, hybrid runtime support, script editors with execution capabilities, debugger, version control using Git, and more. It provides a comprehensive environment for data scientists and AI practitioners to develop, test, and deploy machine learning models and workflows efficiently.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

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.

Auto Data is a library designed for the automatic generation of realistic datasets, essential for the fine-tuning of Large Language Models (LLMs). This highly efficient and lightweight library enables the swift and effortless creation of comprehensive datasets across various topics, regardless of their size. It addresses challenges encountered during model fine-tuning due to data scarcity and imbalance, ensuring models are trained with sufficient examples.

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.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

The `xaitk-saliency` package is an open source Explainable AI (XAI) framework for visual saliency algorithm interfaces and implementations, designed for analytics and autonomy applications. It provides saliency algorithms for various image understanding tasks such as image classification, image similarity, object detection, and reinforcement learning. The toolkit targets data scientists and developers who aim to incorporate visual saliency explanations into their workflow or product, offering both direct accessibility for experimentation and modular integration into systems and applications through Strategy and Adapter patterns. The package includes documentation, examples, and a demonstration tool for visual saliency generation in a user-interface.

PyCM is a Python library for multi-class confusion matrices, providing support for input data vectors and direct matrices. It is a comprehensive tool for post-classification model evaluation, offering a wide range of metrics for predictive models and accurate evaluation of various classifiers. PyCM is designed for data scientists who require diverse metrics for their models.

I'm Richard, your engaging and recommendable data science expert.

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

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A serious interviewer

A Data Science interviewer

Beyond analysis, I deliver insights.

Evolves with user interactions in data science.

Interviewer or interviewee in data science.

Data science co-pilot specializing in statistical modeling and machine learning.

Guide on AI implementation for secure data, with a focus on best practices and tools.

Secure, innovative GPT for collaborative data science and education.

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

Your interactive data analysis expert

I'm the data, image, or document you uploaded, talking to you.

Reviews open data using uploaded knowledge.

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Guiding through data analysis and storytelling.