Best Application Development Software for Domino Enterprise MLOps Platform

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.

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.

MATLAB®, a combination of a desktop environment for iterative analysis, design processes, and a programming language that expresses matrix or array mathematics directly, is MATLAB®. It also includes the Live Editor, which allows you to create scripts that combine output, code, and formatted text in an executable notebook. MATLAB toolboxes have been professionally developed, tested and documented. MATLAB apps allow you to see how different algorithms interact with your data. You can repeat the process until you get the results you desire. Then, MATLAB will automatically generate a program to replicate or automate your work. With minor code changes, you can scale your analyses to run on GPUs, clusters, and clouds. You don't need to rewrite any code or learn big-data programming and other out-of-memory methods. Convert MATLAB algorithms automatically to C/C++ and HDL to run on your embedded processor/FPGA/ASIC. Simulink works with MATLAB to support Model-Based Design.

GitLab is a complete DevOps platform. GitLab gives you a complete CI/CD toolchain right out of the box. One interface. One conversation. One permission model. GitLab is a complete DevOps platform, delivered in one application. It fundamentally changes the way Security, Development, and Ops teams collaborate. GitLab reduces development time and costs, reduces application vulnerabilities, and speeds up software delivery. It also increases developer productivity. Source code management allows for collaboration, sharing, and coordination across the entire software development team. To accelerate software delivery, track and merge branches, audit changes, and enable concurrent work. Code can be reviewed, discussed, shared knowledge, and identified defects among distributed teams through asynchronous review. Automate, track, and report code reviews.

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.

Jira is a project management tool that allows you to plan and track the work of your entire team. Atlassian's Jira is the #1 tool for software development teams to plan and build great products. Jira is trusted by thousands of teams. It offers a range of tools to help plan, track, and release world-class software. It also allows you to capture and organize issues, assign work, and follow team activity. It integrates with leading developer software for end-toend traceability. Jira can help you break down big ideas into manageable steps, whether they are small projects or large cross-functional programs. Organize your work, create milestones and dependencies, and more. Linking work to goals allows everyone to see how their work contributes towards company objectives, and to stay aligned with what's important. Your next step, suggested by AI. Atlassian Intelligence automatically suggests tasks to help you get your big ideas done.

Bitbucket goes beyond Git code management. Bitbucket is a place for teams to plan projects, collaborate on code and test, and then deploy. For small teams of less than 5, Bitbucket is free. Premium plans ($6/user/mo), and Standard ($3/user/mo), are available at scale. You can organize your projects by creating Bitbucket branches from Jira issues and Trello cards. Integrated CI/CD allows you to build, test, and deploy. Configuration as code allows for fast feedback loops and benefits. Pull requests make it easier to approve code reviews. With inline comments, create a merge list with the designated approvers. Bitbucket Pipelines with CI/CD lets you build, test, and deploy with integrated CI/CD. You can benefit from configuration as code and quick feedback loops. With IP whitelisting, 2-step verification and IP whitelisting, you can be sure that your code is safe in the Cloud. You can restrict access to certain users and control their actions by granting branch permissions and merging checks to quality code.

Flask is a lightweight WSGI framework for web applications. It's easy to use and can scale up to complex applications. It started as a wrapper for Jinja and Werkzeug, and has since grown to be one of the most popular Python web app frameworks. Flask is a suggestion tool that doesn't require any dependencies. The developer can choose the tools and libraries that they prefer. The community has many extensions that make it easy to add new functionality.

Python-sql allows you to create SQL queries in a pythonic manner. Select with where condition, simple selects Select with multiple joins or with join. Select with group_by or select with the output name Select with order_by or sub-select. Select another schema and insert query using default values. Insert query with query and values. Update query with values. Update query with where condition. Update query with from list. Delete query with where condition and delete query using sub-query. Provides limit style and qmark style as well as numeric style.

R is a language and environment that allows for statistical computing and graphics. It is a GNU project that is very similar to the S language environment and environment, which were developed at Bell Laboratories (formerly AT&T now Lucent Technologies) in John Chambers and his colleagues. R can be seen as a different implementation to S. However, most code written for S runs without modification under R. R offers a wide range of statistical (linear, nonlinear modelling and classical statistical tests, time series analysis, classification, clustering and graphic techniques and is extensible. Research in statistical methodology is often done using the S language. R offers an Open Source way to participate in this activity. R's strength is its ability to produce well-designed publications-quality plots, including formulae and mathematical symbols.

Web-based notebook that allows data-driven, interactive data analysis and collaborative documents with SQL and Scala. The IPython interpreter offers a similar user experience to Jupyter Notebook. This release features Note level dynamic form, note comparison comparator, and the ability to run paragraph sequentially instead of simultaneous execution in previous releases. Interpreter lifecycle manager automatically terminates interpreter process upon idle timeout. So resources are released when not in use.