Jupyter Notebook Integrations

Codeium is the modern code superpower. It's a free AI-powered code acceleration toolkit. Codeium currently provides AI-generated autocomplete in more than 20 programming languages (including Python and JS, Java, TS, Java and Go) and integrates directly to the developer's IDE (VSCode, JetBrains or Jupyter notebooks. Colab, Vim / Neoovim, etc. Codeium generates multiline code suggestions in a matter of seconds. This will eliminate the need to search for APIs and documentation, write boilerplate and unit test scripts, and many other tedious or frustrating tasks. Codeium is a training platform that allows you to quickly develop on billions of lines. It also helps you stay in the flow and lets you become the best coder you can be.

Get quality translations for your app, website, game, supporting documentation, and on. Invite your own translation team or work with professional translation agencies within Crowdin. Features that ensure quality translations and speed up the process • Glossary – create a list of terms to get consistent translations • Translation Memory (TM) – no need to translate identical strings • Screenshots – tag source strings to get context-relevant translations • Integrations – set up integration with GitHub, Google Play, API, CLI, Android Studio, and on • QA checks – make sure that all the translations have the same meaning and functions as the source strings • In-Context – proofreading within the actual web application • Machine Translations (MT) – pre-translate via translation engine • Reports – get insights, plan and manage the project Crowdin supports more than 30 file formats for mobile, software, documents, subtitles, graphics and assets: .xml, .strings, .json, .html, .xliff, .csv, .php, .resx, .yaml, .xml, .strings and on.

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Kubernetes (K8s), an open-source software that automates deployment, scaling and management of containerized apps, is available as an open-source project. It organizes containers that make up an app into logical units, which makes it easy to manage and discover. Kubernetes is based on 15 years of Google's experience in running production workloads. It also incorporates best-of-breed practices and ideas from the community. Kubernetes is built on the same principles that allow Google to run billions upon billions of containers per week. It can scale without increasing your operations team. Kubernetes flexibility allows you to deliver applications consistently and efficiently, no matter how complex they are, whether you're testing locally or working in a global enterprise. Kubernetes is an open-source project that allows you to use hybrid, on-premises, and public cloud infrastructures. This allows you to move workloads where they are most important.

Available in more than 20 programming languages, including Python, JavaScript and TypeScript, Ruby, TypeScript, Go, Ruby and many others. BLACKBOX AI code search was created so that developers could find the best code fragments to use when building amazing products. Integrations with IDEs include VS Code and Github Codespaces. Jupyter Notebook, Paperspace, and many more. C#, Java, C++, C# and SQL, PHP, Go and TypeScript are just a few of the languages that can be used to search code in Python, Java and C++. It is not necessary to leave your coding environment in order to search for a specific function. Blackbox allows you to select the code from any video and then simply copy it into your text editor. Blackbox supports all programming languages and preserves the correct indentation. The Pro plan allows you to copy text from over 200 languages and all programming languages.

Project Jupyter is an open-source project that develops open-standards software and services for interactive computing in dozens of programming languages. JupyterLab provides a web-based interactive environment for Jupyter notebooks and code. JupyterLab's user interface is flexible. You can configure and arrange it to support a variety of workflows in data science and scientific computing. JupyterLab can be extended and modified to add new components or integrate with existing ones. Open-source web application, Jupyter Notebook, allows you to create and share documents with live code, equations and visualizations. Data cleaning and transformation, numerical modeling, statistical modeling and data visualization are just a few of the many uses. Jupyter supports more than 40 programming languages, including Python and R, Julia, Scala, and Scala.

Pop!_OS is an operating platform for STEM and creative professionals who use computers to discover and create. Open source software is secure and reliable. Unlock your potential We believe you have a lot, based on your extraordinary curiosity. Pop!_OS is optimized for speed navigation, workspace organization, and a fluid, efficient workflow. Your operating system should encourage discovery and not hinder it. Once you have your wheels turning, you can take the scenic route using dock and touchpad gestures or race along a minimalist track while behind the wheel of a revving keyboard. You can customize your workflow in a variety of ways, including keyboard-driven or mouse-driven. Pop!_OS uses automatic-tiling because it is so time-consuming to organize your work. You could still move, resize and arrange windows manually, but why waste your time when your OS does it automatically?

JupyterHub allows you to create a multi-user hub that spawns, manages and proxies multiple instances the single-user Jupyter notebook servers. JupyterHub was created by Project Jupyter to support many users. The Hub can offer notebook server to a class, a corporate data science group, or a high-performance computing group. JupyterHub does not officially support Windows. JupyterHub may work on Windows if you have a Spawner or Authenticator that works on Windows. However, the default JupyterHub will not. Bugs that are reported on Windows will not get accepted and the test suite won't run on Windows. However, small patches that address minor Windows compatibility issues (such basic installation) may be accepted. We recommend that JupyterHub be run in a Linux VM or docker container for Windows-based systems.

Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack.

Docker eliminates repetitive, tedious configuration tasks and is used throughout development lifecycle for easy, portable, desktop, and cloud application development. Docker's complete end-to-end platform, which includes UIs CLIs, APIs, and security, is designed to work together throughout the entire application delivery cycle. Docker images can be used to quickly create your own applications on Windows or Mac. Create your multi-container application using Docker Compose. Docker can be integrated with your favorite tools in your development pipeline. Docker is compatible with all development tools, including GitHub, CircleCI, and VS Code. To run applications in any environment, package them as portable containers images. Use Docker Trusted Content to get Docker Official Images, images from Docker Verified Publishings, and more.

GitHub is the most trusted, secure, and scalable developer platform in the world. Join millions of developers and businesses who are creating the software that powers the world. Get the best tools, support and services to help you build with the most innovative communities in the world. There's a free option for managing multiple contributors: GitHub Team Open Source. We also have GitHub Sponsors that help you fund your work. The Pack is back. We have partnered to provide teachers and students free access to the most powerful developer tools for the school year. Work for a government-recognized nonprofit, association, or 501(c)(3)? Receive a discount Organization account through us.

All the Python tools in one location. PyCharm will take care of the routine, saving you time. To make the most of PyCharm's productivity features, you should focus on the important things. PyCharm has all the information you need about your code. PyCharm can help you with intelligent code completion, quick error checking and quick fixes, project navigation, and many other things. The IDE allows you to write clean and maintainable code and helps you maintain control of quality with PEP8 tests, testing assistance and smart refactorings. PyCharm was created by programmers for programmers to give you all the tools you need to create Python code. PyCharm offers smart code completion, code inspections and quick-fixes. It also includes automated code refactorings.

Dropbox Business is more than secure file storage. It's a smart workspace that brings together teams, tools, content, and other resources. You can create, store, and share cloud content using Google Docs, Sheets and Slides, Microsoft Office files and Dropbox Paper. Dropbox Spaces allows you to combine cloud content and files, so your PowerPoints can live alongside your Trello boards, Google Docs, and other tools. Access your team's work easily from any computer, mobile device or web browser. Connect tools such as Zoom and Slack to keep your team's files and conversations in one place. Intelligently suggested folders and files keep your team one step ahead. They will have the content they need when they need it. Dropbox offers a secure, distributed infrastructure with admin tools to control and visibility. Keep your company's data safe with Dropbox.

Tabnine is the AI coding assistant that you control — helping development teams of every size use AI to accelerate and simplify the software development process without sacrificing privacy, security, or compliance. Tabnine boosts engineering velocity, code quality, and developer happiness by automating the coding workflow through AI tools customized to your team. Tabnine is trusted by more than 1,000,000 developers across thousands of organizations. Tabnine offers best-in-class AI code completion and an AI-powered chat and supports numerous use cases such as code generation, explanation of code, creating unit tests, generating documentation, debugging code, refactoring and maintaining code. Tabnine is integrated with all the major IDEs such as VS Code, JetBrains, Visual Studio, Eclipse. It supports over 80 programming languages and frameworks including JavaScript, TypeScript, Python, Java, C, C++, C#, Go, Php, Ruby, Kotlin, Dart, Rust, React/Vue, HTML 5, CSS, Lua, Perl, YAML, Cuda, SQL, Scala, Shell (bash), Swift, R, Julia, VB, Groovy, Matlab, Terraform, ABAP and more.

Google Colab is a cloud-based Jupyter Notebook environment that allows users to write and execute Python code without any setup required. It provides access to powerful computing resources, including GPUs and TPUs, making it an excellent tool for machine learning, data analysis, and academic research. Colab is designed for collaborative work, enabling users to share notebooks with others, track changes, and easily integrate with Google Drive for file storage. It is particularly beneficial for both beginners and professionals seeking a free, interactive platform for experimenting with code and data. With Colab notebooks, you can integrate executable code with rich text, images, LaTeX, HTML, and other elements in a single document. All notebooks you create are saved to your Google Drive. Sharing with colleagues or friends is easy, allowing them to comment or edit your work. Additionally, Colab now provides a Data Science Agent that automates the entire analysis process, from data understanding to delivering insights in a functional notebook. (Note: Sequences are shortened, and results are for illustration. The Data Science Agent may occasionally make errors.)

The most complex AI, ML, Deep Learning models can be trained. With just a few clicks, you can scale from a single machine up to a whole fleet of VMs. Lambda Cloud makes it easy to scale up or start your Deep Learning project. You can get started quickly, save compute costs, and scale up to hundreds of GPUs. Every VM is pre-installed with the most recent version of Lambda Stack. This includes major deep learning frameworks as well as CUDA®. drivers. You can access the cloud dashboard to instantly access a Jupyter Notebook development environment on each machine. You can connect directly via the Web Terminal or use SSH directly using one of your SSH keys. Lambda can make significant savings by building scaled compute infrastructure to meet the needs of deep learning researchers. Cloud computing allows you to be flexible and save money, even when your workloads increase rapidly.

Worldwide, hundreds of satisfied customers, tens to millions of requests each day. Here today, here tomorrow. Since 2013, customers have funded the project, not VCs. Redundant EU data center, GDPR compliant. Independently monitored uptime All API requests are encrypted with 256-bit SSL encryption. (HTTPS). Support is available 24/7. Ask us anything. Proud corporate member, OpenStreetMap Foundation. Excellent product. Many open gecoders are behind a single API. The industry's most permissive licensing. You can cache results for as long as necessary. No vendor lock-in. Results can be displayed on any map. All coverage. OpenStreetMap offers continuous updates - OpenStreetMap receives over four million edits per day. Maintaining your own system can be stressful and expensive. Easy setup: Tutorials, SDKs, and FIPS codes for over 30 programming languages. To save engineering time, we add useful information such as calling codes, FIPS codes and speed limits.

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

Coginiti is the AI-enabled enterprise Data Workspace that empowers everyone to get fast, consistent answers to any business questions. Coginiti helps you find and search for metrics that are approved for your use case, accelerating the lifecycle of analytic development from development to certification. Coginiti integrates the functionality needed to build, approve and curate analytics for reuse across all business domains, while adhering your data governance policies and standards. Coginiti’s collaborative data workspace is trusted by teams in the insurance, healthcare, financial services and retail/consumer packaged goods industries to deliver value to customers.

Explore a new library and dataset in a notebook. A 2orkflow automates preprocessing, training, and testing. A deployment brings your application to life. You can use notebooks, workflows, or deployments separately. Compatible with all. Gradient is compatible with all major frameworks. Gradient is powered with Paperspace's top-of-the-line GPU instances. Source control integration makes it easier to move faster. Connect to GitHub to manage your work and compute resources using git. In seconds, you can launch a GPU-enabled Jupyter Notebook directly from your browser. Any library or framework is possible. Invite collaborators and share a link. This cloud workspace runs on free GPUs. A notebook environment that is easy to use and share can be set up in seconds. Perfect for ML developers. This environment is simple and powerful with lots of features that just work. You can either use a pre-built template, or create your own. Get a free GPU

Giskard provides interfaces to AI & Business teams for evaluating and testing ML models using automated tests and collaborative feedback. Giskard accelerates teamwork to validate ML model validation and gives you peace-of-mind to eliminate biases, drift, or regression before deploying ML models into production.

AI allows you to build fast and produce high quality code. Create high-quality code quickly. AI Autocomplete allows you to quickly prototype. AI Autocomplete transforms your prototype into a production-quality code. Our specialized neural networks reduce the time spent on boilerplate and on StackOverFlow. Refactor, document, add types. To modify your code, give instructions directly to the AI. Are you tired of writing tests? We've got you covered. Automate the generation of unit tests using AI and metaprogramming. We believe that AI is the future of software development. Our long-term goal is to allow programmers to think at the speed of thought. We believe that the AI advances will open up new programming methods beyond the pre-AI accelerated stack. These new programming methods won't look like an IDE or version control system.

Akira.ai delivers Agentic AI solutions that integrate autonomous AI agents into business processes to improve operational efficiency. These AI agents help automate tasks, generate insights, and assist with decision-making, thereby allowing teams to focus on strategic objectives. Akira’s platform seamlessly integrates with existing enterprise systems, optimizing workflows in industries ranging from manufacturing to telecom. By empowering organizations with AI-driven automation and real-time problem-solving capabilities, Akira fosters enhanced productivity, scalability, and faster decision-making.

Select the configurations and resources required for specific code segments within your project. It only takes seconds to save and apply changes in a training scenario. Select the right configuration of computing resources to launch training models in a matter of seconds. All will be created automatically, without the need to manage infrastructure. Select a serverless or dedicated operating mode. All in one interface, manage project data, save to datasets and connect to databases, object storage or other repositories. Create a ML model with colleagues from around the world, share the project and set budgets across your organization. Launch your ML within minutes, without developers' help. Try out experiments with different models being published simultaneously.

Installed with one click, it's a desktop application that includes Jupyter Notebook. It has interactive code snippets, an AI assistant and a coding speed-up tool. Over 100 interactive code recipes have been handcrafted by us and can be used in Data Science projects. Code recipes detect the packages that are available in the current environment. Install modules with a single click. You can create variables and interact with them in your Python session. Interactive recipes speed-up your work. AI Assistant can access your current Python session and variables. It is smarter because it has a broad context. Our AI Assistant is designed to solve data issues using Python programming language. It can assist you with plots and data loading, data wrangling and Machine Learning. Click the Fix button to use AI to quickly fix code issues. The AI assistant will analyze and suggest a solution to the error.

Scout is an all-encompassing platform that allows users to efficiently build, launch and scale AI solutions. It has a workflow creator for creating AI automations based on models, web scraping and data storage, APIs, and custom logic. Users can automate content ingestion, such as from websites and documentation. They can also connect multiple large language model within a single workflow, to find optimal solutions. Copilots, which delivers AI-generated responses directly on websites, as well as Slack integration, for customer interaction, are some of the deployment options. APIs and SDKs can be used to build custom AI applications. Scout offers comprehensive testing and tuning tools, including evaluations and real-time monitoring. It also has built-in logging for workflow status, cost, and latency. The platform is trusted and used by teams who are building the future.

Stata is a comprehensive, integrated software package that can handle all aspects of data science: data manipulation, visualization and statistics, as well as automated reporting. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

TENGU is a Data orchestration platform that serves as a central workspace for all data profiles to work more efficiently and enhance collaboration. Allowing you to get the most out of your data, faster. It allows complete control over your data environment in an innovative graph view for intuitive monitoring. Connecting all necessary tools in one workspace. It enables self-service, monitoring and automation, supporting all data roles and operations from integration to transformation.

data.world is a fully managed cloud service that was built for modern data architectures. We handle all updates, migrations, maintenance. It is easy to set up with our large and growing network of pre-built integrations, including all the major cloud data warehouses. Your team must solve real business problems and not struggle with complicated data software when time-to value is important. data.world makes it simple for everyone, not just the "data people", to get clear, precise, and fast answers to any business question. Our cloud-native data catalog maps siloed, distributed data to consistent business concepts, creating an unified body of knowledge that anyone can understand, use, and find. Data.world is the home of the largest open data community in the world. It is where people come together to work on everything, from data journalism to social bot detection.

DSVMs are Azure Virtual Machine Images that have been pre-configured, configured, and tested with many popular tools that are used for data analytics and machine learning. A consistent setup across the team promotes collaboration, Azure scale, management, Near-Zero Setup and full cloud-based desktop to support data science. For one to three classroom scenarios or online courses, it is easy and quick to set up. Analytics can be run on all Azure hardware configurations, with both vertical and horizontal scaling. Only pay for what you use and when you use it. Pre-configured Deep Learning tools are readily available in GPU clusters. To make it easy to get started with the various tools and capabilities, such as Neural Networks (PYTorch and Tensorflow), templates and examples are available on the VMs. ), Data Wrangling (R, Python, Julia and SQL Server).

SensorCloud is a unique platform for remote management, storage, and visualization of sensor data. It leverages powerful Cloud computing technologies to offer exceptional data scalability, rapid visualization, user-programmable analysis, and data scalability. SensorCloud's core features are FastGraph, MathEngine®, LiveConnect and the OpenData API. SensorCloud makes it easy to create dashboards that display all your data. You can create dashboards with as little as a Timeseries Graph widget or more complex features such as Radial Gauges and Text Charts, Linear Gauges and FFTs, Statistics, and so on. SensorCloud allows you upload as much data you like, and LORD's sensors can sample very fast, so it was important that you could quickly visualize large amounts of data. We were unable to find an application that could handle even a few gigabytes, so we created our own algorithm.

It takes a lot of time and resources to install and configure today's complex software technology platforms. Xtendlabs is different. Xtendlabs Emerging Technology Platform-as-a-Services provides immediate access to emerging Big Data, Data Sciences, and Database technology platforms online, from any device and location, 24/7. Xtendlabs can be accessed 24/7 from any location, whether it is your home, office, or on the road. Xtendlabs can scale to your needs on-demand so you can concentrate on your business problem and learning, rather than trying to set up infrastructure. Sign-in to immediately access your virtual lab environment. Xtendlabs does not require virtual machine installation, configuration or system setup, which saves valuable time and money. Pay as you go each month. Xtendlabs does not require upfront investments in hardware or software.

EOfactory lets you use your data or subscribe to our data delivery services. Our platform can access multiple public and private data sources to extract and analyze information. Using our ARD toolkit, EOfactory makes it easy to prepare analysis-ready data. No more time spent on data processing. Now you can concentrate on getting the best results. EOfactory lets you build your own time models using interactive AI/ML tools. This will help you create the best EO-machine learning models. EOfactory offers a variety pre-built models that have been developed by subject matter specialists and are specific to specific geographical regions. Democratizing earth observation intelligence to ensure a sustainable future. Our studio can help you create a customized UI/ UX and an intuitive dashboard to visualize the results. Cloud removal, cloud shadow removal and machine learning downscale.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Transform your equipment data to competitive advantage. This technology is used on more than 1 million assets. The most advanced predictive operations technology is available to power your continuous improvement. The production environment of today is more complex and interconnected than ever before. Your plant floor generates an inordinate amount of data, from increasingly sophisticated PLC technology to the ever-expanding IIoT world. It can be difficult to distinguish the meaningful information from the noise when there is so much information coming in from business, supply chain, and financial systems. TwinThread enables you to transform data from any source into actionable and impactful positive results. Our predictive operations platform was built from the ground up to increase operational efficiency, reduce costs, improve consistency, and increase throughput. As bold as it sounds, our mission is to achieve 100% plant efficiency.

Lodestar is a complete solution for creating computer vision models from video data. The world's first active learning data annotation platform allows you to label hours of video and speed up the creation of high-quality datasets and computer vision models. Automated data preparation makes it easy to drag and drop 10 hours worth of video into one project. Multiple video formats are supported and no data curation is required. Annotators and data scientists can collaborate to create a functional object detection model within an hour by using continuous model training and a shared managed dataset. Every plan comes with unlimited labels.

Neptune.ai, a platform for machine learning operations, is designed to streamline tracking, organizing and sharing of experiments, and model-building. It provides a comprehensive platform for data scientists and machine-learning engineers to log, visualise, and compare model training run, datasets and hyperparameters in real-time. Neptune.ai integrates seamlessly with popular machine-learning libraries, allowing teams to efficiently manage research and production workflows. Neptune.ai's features, which include collaboration, versioning and reproducibility of experiments, enhance productivity and help ensure that machine-learning projects are transparent and well documented throughout their lifecycle.

Intel®, DevCloud provides free access to a variety of Intel®, architectures. This allows you to get hands-on experience using Intel®, software, and execute your edge and AI, high-performance computing, (HPC) and rendering workloads. You have all the tools and libraries you need to accelerate your learning and project prototyping with preinstalled Intel®. optimized frameworks, tools and libraries. Freely learn, prototype, test, run and manage your workloads on a cluster with the latest Intel®, hardware and software. A new collection of curated experiences will help you learn, including market vertical samples and Jupyter Notebook tutorials. You can build your solution in JupyterLab, test it with bare metal, or create a containerized solution. You can quickly bring it to Intel DevCloud to be tested. Use the deep learning toolbench to optimize your solution for a specific target device edge. Take advantage of the new, stronger telemetry dashboard.

You can take control of your product analytics and self-service optimization using no-ETL integration. Your data is not yours. Blackbox solution processes your data, hiding how metrics are calculated. Your insights are impossible to reconcile because of siloed analytics practices. No retrospective analysis, no data backfill. Communication gaps and delays can be caused by non-exploratory, self-service analytics. Kubit's no ETL platform integrates directly with your existing data model, allowing self-service product analytics that drive engagement and improve retention. Templates that are ready-to-use for query, funnel and path, retention, as well as cohort analyses. This template is for product people who want to quickly explore data and find insights. Kubit connects directly to your cloud data warehouse without the requirement for SDK or ETL jobs. We make the most of the rich data model that you already have. Our machine learning-based algorithms can quickly detect anomalies and provide answers.

One development environment for all data science workflows. Natively analyze your data without the need to switch between services. Data to training at scale Models can be built and trained 5X faster than traditional notebooks. Scale up model development using simple connectivity to Vertex AI Services. Access to data is simplified and machine learning is made easier with BigQuery Dataproc, Spark and Vertex AI integration. Vertex AI training allows you to experiment and prototype at scale. Vertex AI Workbench allows you to manage your training and deployment workflows for Vertex AI all from one location. Fully managed, scalable and enterprise-ready, Jupyter-based, fully managed, scalable, and managed compute infrastructure with security controls. Easy connections to Google Cloud's Big Data Solutions allow you to explore data and train ML models.

Coiled makes enterprise-grade Dask easy. Coiled manages Dask clusters within your AWS or GCP account. This makes it the easiest and most secure method to run Dask in production. Coiled manages your cloud infrastructure and can deploy to your AWS account or Google Cloud account in a matter of minutes. Coiled provides a solid deployment solution that requires little effort. You can customize the cluster node types to meet your analysis needs. Run Dask in Jupyter Notebooks to get real-time dashboards, cluster insights, and other useful information. You can easily create software environments with custom dependencies for your Dask analysis. Enjoy enterprise-grade security. SLAs, user level management, and auto-termination clusters reduce costs. Coiled makes it easy for you to deploy your cluster on AWS and GCP. It takes only minutes and requires no credit card. You can launch code from anywhere you like, including cloud services like AWS SageMaker and open source solutions like JupyterHub.

Lepton is an open source project on GitHub. It's free, and we don’t accept donations. Wikimedia Foundation can be donated if you wish. This foundation helps to sustain free knowledge through Wikipedia, its sister projects, and other resources for people all over the world. Lepton replies to GitHub APIs to identify the language. Leptonis a central configuration file for Lepton that is parsed at the app start. The file is not automatically generated. Lepton is a desktop client of GitHub Gist that does not have its own service. All data are saved locally or in GitHub Gist. Create a GitHub token that has gist enabled. Place the token and any other configurations in the enterprise section of the Lepton config file. Lepton supports a formatted description section, with title and tag support. You can group your gists according to their languages and custom tags. Letpon supports Markdown rendering. Lepton can be used for markdown note-taking, and you can access it anywhere.

We've been working on Generative AI for 5 years. Deep Lake combines the power and flexibility of vector databases and data lakes to create enterprise-grade LLM-based solutions and refine them over time. Vector search does NOT resolve retrieval. You need a serverless search for multi-modal data including embeddings and metadata to solve this problem. You can filter, search, and more using the cloud, or your laptop. Visualize your data and embeddings to better understand them. Track and compare versions to improve your data and your model. OpenAI APIs are not the foundation of competitive businesses. Your data can be used to fine-tune LLMs. As models are being trained, data can be efficiently streamed from remote storage to GPUs. Deep Lake datasets can be visualized in your browser or Jupyter Notebook. Instantly retrieve different versions and materialize new datasets on the fly via queries. Stream them to PyTorch, TensorFlow, or Jupyter Notebook.

Robocorp's Open Source Gen2 RPA platform is faster, more cost-effective, and built for developers and teams who want to work smarter and not harder. Teams can create, optimize and accelerate automation while reducing the infrastructure burden required to run Gen1 RPA. Robocorp users can save up to 80% on what they would have paid for Gen1 tools. Robocorp technology allows developers to create any automation their team can imagine. Our programmable solution leverages an open-source ecosystem that is rich in libraries and keywords. This gives you the flexibility you need to build automation you can rely on. Our RPA automation stack is built using Python. Robocorp allows developers to build, integrate and deploy complex automation quickly. Monitor, manage and visualize your automation from a single window.

Kedro provides the foundation for clean, data-driven code. It applies concepts from software engineering to machine-learning projects. Kedro projects provide scaffolding for complex machine-learning and data pipelines. Spend less time on "plumbing", and instead focus on solving new problems. Kedro standardizes the way data science code is written and ensures that teams can collaborate easily to solve problems. You can make a seamless transition between development and production by using exploratory code. This code can be converted into reproducible, maintainable and modular experiments. A series of lightweight connectors are used to save and upload data across a variety of file formats and file systems.

Voxel51, the company behind FiftyOne is responsible for the open-source software that allows you to create better computer vision workflows through improving the quality of datasets and delivering insights into your models. Explore, search and slice your datasets. Find samples and labels quickly that match your criteria. FiftyOne offers tight integrations to public datasets such as COCO, Open Images and ActivityNet. You can also create your own datasets. Data quality is one of the most important factors that affect model performance. FiftyOne can help you identify, visualize and correct the failure modes of your model. Annotation errors lead to bad models. But finding mistakes manually is not scalable. FiftyOne automatically finds and corrects label mistakes, so you can curate better-quality datasets. Manual debugging and aggregate performance metrics don't scale. Use the FiftyOne Brain for edge cases, new samples to train on, and more.

Datafi is a platform that provides a unified data environment for business teams. It integrates data silos, unifies data security, and enables self-service workflows to meet the unique needs of business users who want to find, use, or share the information they need. Datafi is used by customers to increase their organization's data capabilities, and empower more employees to make better and faster data-driven decision. Datafi makes data easily accessible and meaningful to everyone. Know how your data will be accessed and used. Data-forward companies know how important it is to enable their data to drive business outcomes. This starts with enabling easy and secure data access. Data-driven insights can lead to new business outcomes. Organizations that improve their data literacy will be more likely to discover these data-driven insights.

PostgresML is an entire platform that comes as a PostgreSQL Extension. Build simpler, faster and more scalable model right inside your database. Explore the SDK, and test open-source models in our hosted databases. Automate the entire workflow, from embedding creation to indexing and Querying for the easiest (and fastest) knowledge based chatbot implementation. Use multiple types of machine learning and natural language processing models, such as vector search or personalization with embeddings, to improve search results. Time series forecasting can help you gain key business insights. SQL and dozens regression algorithms allow you to build statistical and predictive models. ML at database layer can detect fraud and return results faster. PostgresML abstracts data management overheads from the ML/AI cycle by allowing users to run ML/LLM on a Postgres Database.