Best Data Science Software for Linux

Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.

Bring data analysts, engineers, and scientists together. Enable self-service analytics and operationalize machine learning. Get results today and build for tomorrow. Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) or a customizable drag-and-drop visual interface at any step of the predictive dataflow prototyping process – from wrangling to analysis to modeling. Profile the data visually at every step of the analysis. Interactively explore and chart your data using 25+ built-in charts. Prepare, enrich, blend, and clean data using 80+ built-in functions. Leverage Machine Learning technologies (Scikit-Learn, MLlib, TensorFlow, Keras, etc.) in a visual UI. Build & optimize models in Python or R and integrate any external ML library through code APIs.

Datalore is a collaborative data science and analytics platform aimed at boosting the whole analytics workflow and making work with data enjoyable for both data scientists and data savvy business teams across the enterprise. Keeping a major focus on data teams workflow, Datalore offers technical-savvy business users the ability to work together with data teams, using no-code or low-code together with the power of Jupyter notebooks. Datalore enables analytical self-service for business users, enabling them to work with data using SQL and no-code cells, build reports and deep dive into data. It offloads the core data team with simple tasks. Datalore enables analysts and data scientists to share results with ML Engineers. You can run your code on powerful CPUs or GPUs and collaborate with your colleagues in real-time.

Coder delivers self-hosted cloud development environments consistently provisioned as code and pre-deployed for developer activity on day one. Preferred by enterprises, Coder is open source and runs air-gapped on-premise or in your cloud, giving developers access to powerful infrastructure without compromising governance. Coder moves local development and source code to your centralized infrastructure where developers can access their remote environments via their favorite desktop or web-based IDE. This is the optimal intersection of improved developer experience, productivity, and security. Coder’s ephemeral development environments are provisioned as code from pre-defined templates, which means developers can create a new workspace with a click. Now, they can avoid days or weeks struggling with local dependency versioning conflicts or security approvals. With Coder, developers can onboard or shift between projects in minutes.

Stata is a complete, integrated software package that provides all your data science needs: data manipulation, visualization, statistics, and automated reporting. Stata is fast and accurate. It is easy to learn through the extensive graphical interface yet completely programmable. With Stata's menus and dialogs, you get the best of both worlds. You can easily point and click or drag and drop your way to all of Stata's statistical, graphical, and data management features. Use Stata's intuitive command syntax to quickly execute commands. Whether you enter commands directly or use the menus and dialogs, you can create a log of all actions and their results to ensure the reproducibility and integrity of your analysis. Stata also has complete command-line scripting and programming facilities, including a full matrix programming language. You have access to everything you need to script your analysis or even to create new Stata commands--commands that work just like those shipped with Stata.

DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.

Kedro is the foundation for clean data science code. It borrows concepts from software engineering and applies them to machine-learning projects. A Kedro project provides scaffolding for complex data and machine-learning pipelines. You spend less time on tedious "plumbing" and focus instead on solving new problems. Kedro standardizes how data science code is created and ensures teams collaborate to solve problems easily. Make a seamless transition from development to production with exploratory code that you can transition to reproducible, maintainable, and modular experiments. A series of lightweight data connectors is used to save and load data across many different file formats and file systems.

With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.

SAS® Viya® data science offerings provide a comprehensive, scalable analytics environment that's quick and easy to deploy, enabling you to meet diverse business needs. Automatically generated insights enable you to identify the most common variables across all models, the most important variables selected across models and assessment results for all models. Natural language generation capabilities are used to create project summaries written in plain language, enabling you to easily interpret reports. Analytics team members can add project notes to the insights report to facilitate communication and collaboration among team members. SAS lets you embed open source code within an analysis and call open source algorithms seamlessly within its environment. This facilitates collaboration across your organization because users can program in their language of choice. You can also take advantage of SAS Deep Learning with Python (DLPy), our open-source package on GitHub.

Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.

Microsoft continues its commitment and development in R, not only in the latest Machine Learning Server release, but also in the newest Microsoft R Client and Microsoft R Open releases. You can also find R and Python support in SQL Server Machine Learning Services on Windows and Linux, and R support in Azure SQL Database. R components are backwards compatible. You should be able to run existing R script on newer versions, with the exception of dependencies on packages or platforms that are no longer supported, or known issues that require a workaround or code change. Microsoft R Open is the enhanced distribution of R from Microsoft Corporation. The current release, Microsoft R Open 4.0.2, is based the statistical language R-4.0.2 and includes additional capabilities for improved performance, reproducibility and platform support. Compatibility with all packages, scripts and applications that work with R-4.0.2.

Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance.

Amadea technology relies on the fastest real-time calculation and modeling engine on the market. Speed up the creation, deployment and automation of your analytics projects within the same integrated environment. Data quality is the key to analytical projects. Thanks to the ISoft real-time calculation engine, the fastest on the market, Amadea allows companies to prepare and use massive and/or complex data in real-time, regardless of the volume. ISoft started from a simple observation, successful analytical projects must involve the business users at every stage. Founded on a no-code interface, accessible to all types of users, Amadea allows everyone involved in analytical projects to take part. As Amadea has the fastest real-time calculation engine on the market, it lets you specify, prototype and build your data applications simultaneously. Amadea incorporates the fastest real-time data analysis engine on the market, 10 million lines per second & per core for standard calculations.