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Data Science Software
Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends.
Computer Vision Software
Computer vision software allows machines to interpret and analyze visual data from images or videos, enabling applications like object detection, image recognition, and video analysis. It utilizes advanced algorithms and deep learning techniques to understand and classify visual information, often mimicking human vision processes. These tools are essential in fields like autonomous vehicles, facial recognition, medical imaging, and augmented reality, where accurate interpretation of visual input is crucial. Computer vision software often includes features for image preprocessing, feature extraction, and model training to improve the accuracy of visual analysis. Overall, it enables machines to "see" and make informed decisions based on visual data, revolutionizing industries with automation and intelligence.
AI Coding Assistants
AI coding assistants are software tools that use artificial intelligence to help developers write, debug, and optimize code more efficiently. These assistants typically offer features like code auto-completion, error detection, suggestion of best practices, and code refactoring. AI coding assistants often integrate with integrated development environments (IDEs) and code editors to provide real-time feedback and recommendations based on the context of the code being written. By leveraging machine learning and natural language processing, these tools can help developers increase productivity, reduce errors, and learn new programming techniques.
View more categories (5) for "python regex"
127 Products for "python regex" with 1 filter applied:
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1
MakerSuite
Google
...With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js. -
2
Polars
Polars
Knowing of data wrangling habits, Polars exposes a complete Python API, including the full set of features to manipulate DataFrames using an expression language that will empower you to create readable and performant code. Polars is written in Rust, uncompromising in its choices to provide a feature-complete DataFrame API to the Rust ecosystem. Use it as a DataFrame library or as a query engine backend for your data models. -
3
Studio 3T
Studio 3T
...Break down aggregation queries into manageable steps and build them stage by stage, for easier debugging and querying. Generate instant code in JavaScript (Node.js), Java (2.x and 3.x driver API), Python, C#, PHP, and Ruby from MongoDB and SQL queries that you can copy and paste into your application. Save MongoDB imports, exports, data comparisons, and migrations as tasks that you can run on demand. Or even better, skip the reminders and schedule them to run exactly when you need them. Make changes to your collection’s schema in just a few clicks, perfect for schema performance tuning, restructuring, or cleaning up after data migration.Starting Price: $499/year/user -
4
FrameworX
Tatsoft
...Designed for edge-to-enterprise use, it unifies operations, data, and AI under one scalable, .NET-based architecture. Features include real-time data modeling, historian, alarms, reports, audit trails, scripting in C#, VB.NET, JavaScript, and Python, plus 100+ native drivers for PLCs, DCS, OPC, and MQTT (broker/client/SparkplugB). Build once—deploy anywhere with zero client installs and full web, mobile, and desktop access. Includes every module from day one: Devices, Alarms, Historian, Reports, Security, and DevOps tools. Proven in 5,000+ global deployments, FrameworX powers mission-critical operations across industries with reliability, unlimited scalability, and transparent licensing. ...Starting Price: $750 -
5
SQLAlchemy
SQLAlchemy
SQLAlchemy is the Python SQL toolkit and object-relational mapper that gives application developers the full power and flexibility of SQL. SQL databases behave less like object collections the more size and performance start to matter; object collections behave less like tables and rows the more abstraction starts to matter. SQLAlchemy aims to accommodate both of these principles. -
6
Amazon MWAA
Amazon
...Apache Airflow is an open-source tool used to programmatically author, schedule, and monitor sequences of processes and tasks referred to as “workflows.” With Managed Workflows, you can use Airflow and Python to create workflows without having to manage the underlying infrastructure for scalability, availability, and security. Managed Workflows automatically scales its workflow execution capacity to meet your needs, and is integrated with AWS security services to help provide you with fast and secure access to data.Starting Price: $0.49 per hour -
7
Seaborn
Seaborn
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. For a brief introduction to the ideas behind the library, you can read the introductory notes or the paper. Visit the installation page to see how you can download the package and get started with it. -
8
...Storage scaling, query execution, and backup layers are fully automated. The compatibility of the service API in serverless mode allows you to use the AWS SDKs for Java, JavaScript, Node.js, .NET, PHP, Python, and Ruby. YDB is hosted in three availability zones, ensuring availability even if a node or availability zone goes offline. If equipment or a data center fails, the system automatically recovers and continues working. YDB is tailored to meet high-performance requirements and can process hundreds of thousands of transactions per second with low latency. ...
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9
Omniscope Evo
Visokio
...Omniscope is not only an all-in-one BI tool with a responsive UX on all modern devices, but also a powerful and extensible platform: you can augment data workflows with Python / R scripts and enhance reports with any JS visualisation. Whether you’re a data manager, scientist or analyst, Omniscope is your complete solution: from data, through analytics to visualisation.Starting Price: $59/month/user -
10
Kyoto Tycoon
Altice Labs
...It has its own fully-featured protocol based on HTTP and a (limited) binary protocol for even better performance. There are several client libraries implementing them for multiple languages (we're maintaining one for Python here). It can also be configured with simultaneous support for the memcached protocol, with some limitations on available data update commands. This is useful if you wish to replace memcached in larger-than-memory/persistency scenarios. Here you can find improved versions of the latest available upstream releases, intended to be used together and tested in real-world production environments. ... -
11
Azure Databricks
Microsoft
Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. ... -
12
Cloudera Data Science Workbench
Cloudera
Accelerate machine learning from research to production with a consistent experience built for your traditional platform. With Python, R, and Scala directly in the web browser, Cloudera Data Science Workbench (CDSW) delivers a self-service experience data scientists will love. Download and experiment with the latest libraries and frameworks in customizable project environments that work just like your laptop. Cloudera Data Science Workbench provides connectivity not only to CDH and HDP but also to the systems your data science teams rely on for analysis. ... -
13
Superlinked
Superlinked
...Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
14
ThinkSQL
ThinkSQL
...The server also has stored procedures and functions (using the standard syntax), and has support for large multimedia objects. It's easy to install, runs on Windows ® and Linux ®, and has native ODBC, JDBC™, dbExpress™ and Python drivers so your applications can connect directly from any platform. -
15
esProc
Raqsoft
esProc is a professional structured computing tool, which is ready to use, built-in with SPL language more natural and easier to use than python. The more complex data processing is, the more obvious the features of simple SPL syntax and clear steps are. You can observe the result for each action and controlled the calculation process at will according to the outcome. It is especially suitable to solve the problem of order-related calculation, such as the typical problems in desktop data analysis: same period ratio, ratio compared to last period, relative interval data retrieving, ranking in groups, TopN in groups. esProc can directly process the data files such as CSV, Excel, JSON, and XML. -
16
Sparksee
Sparsity Technologies
Sparksee (formerly known as DEX), makes space and performance compatible with a small footprint and a fast analysis of large networks. It is natively available for .Net, C++, Python, Objective-C and Java, and covers the whole spectrum of Operating Systems. The graph is represented through bitmap data structures that allow high compression rates. Each of the bitmaps is partitioned into chunks that fit into disk pages to improve I/O locality. Using bitmaps, operations are computed with binary logic instructions that simplify the execution in pipelined processors. ... -
17
Oracle Big Data Service
Oracle
...Quickly create Hadoop-based data lakes to extend or complement customer data warehouses, and ensure that all data is both accessible and managed cost-effectively. Query, visualize and transform data so data scientists can build machine learning models using the included notebook with its R, Python and SQL support. Move customer-managed Hadoop clusters to a fully-managed cloud-based service, reducing management costs and improving resource utilization.Starting Price: $0.1344 per hour -
18
Redgate SQL Data Generator
Redgate Software
...Greater flexibility and manual control for creating foreign key data. Shareable custom generators – save regexp and SQL statement generators to share with your team. Write your own custom generators in Python, so you can create any extra data you need. Seeded random data generation allows you to generate the same collection of data every time. Foreign key support for generating consistent data across multiple tables.Starting Price: $405 per user per year -
19
ActiveViam
ActiveViam
...Gain consolidated, in-depth insights into risk metrics across all systems for real-time front-office trading and intraday risk management. Optimize capital allocation and ensure regulatory compliance with FRTB, LCR, IFRS 9 and more. Based on our proprietary ActivePivot technology, leveraging Python and Java with a strong focus on collaboration, Atoti+ brings together the builders and consumers of analytics applications to accelerate and streamline the design and development process. Innovative data analytics that empower financial services firms to be ready for the unexpected. Integrates with existing databases, risk engines and BI tools. -
20
Dask
Dask
Dask is open source and freely available. It is developed in coordination with other community projects like NumPy, pandas, and scikit-learn. Dask uses existing Python APIs and data structures to make it easy to switch between NumPy, pandas, scikit-learn to their Dask-powered equivalents. Dask's schedulers scale to thousand-node clusters and its algorithms have been tested on some of the largest supercomputers in the world. But you don't need a massive cluster to get started. Dask ships with schedulers designed for use on personal machines. ... -
21
pandas
pandas
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. ... -
22
Azure Data Lake Analytics
Microsoft
Easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and .NET over petabytes of data. With no infrastructure to manage, you can process data on demand, scale instantly, and only pay per job. Process big data jobs in seconds with Azure Data Lake Analytics. There is no infrastructure to worry about because there are no servers, virtual machines, or clusters to wait for, manage, or tune.Starting Price: $2 per hour -
23
Metaflow
Metaflow
Successful data science projects are delivered by data scientists who can build, improve, and operate end-to-end workflows independently, focusing more on data science, less on engineering. Use Metaflow with your favorite data science libraries, such as Tensorflow or SciKit Learn, and write your models in idiomatic Python code with not much new to learn. Metaflow also supports the R language. Metaflow helps you design your workflow, run it at scale, and deploy it to production. It versions and tracks all your experiments and data automatically. It allows you to inspect results easily in notebooks. Metaflow comes packaged with the tutorials, so getting started is easy. ... -
24
RestApp
RestApp
...RestApp enables Data & Ops teams to activate data in minutes with No-Code by: - Connecting with your favorite databases and business apps - Modeling your data with drag-and-drop SQL, NoSQL and Python functions and then easily creating and sharing your queries with your teammates - Syncing automatically your data with your tools. With RestApp, you are notably able by using our templates to: - Computing your main financial KPIs: churn rate, MRR, ARR, ACV, ARPU, LVT - Computing your customers’ lead scoring - Generate automatic cohort analysisStarting Price: Free -
25
Equifax Ignite for Financial Services
Equifax for FinTech
...Create powerful analyses, understand trends within financial services, and discover how well you are performing in certain areas relative to your peer groups. Explore many of our powerful data assets by using industry standard tools such as Python® and BigQuery. Then leverage even more automation power with Attribute Engine and Advanced Model Engine from Equifax. -
26
Alembic
Alembic
Alembic is a lightweight database migration tool that can be used with the SQLAlchemy database toolkit for Python. Alembic is written by the author of SQLAlchemy. While Alembic can be installed system-wide, it’s more common that it’s installed locally in a virtual environment, as it also uses libraries such as SQLAlchemy and database drivers that are more appropriate for local installations. Can emit statements to a database in order to change the structure of tables and other constructs. ...Starting Price: Free -
27
VectorDB
VectorDB
VectorDB is a lightweight Python package for storing and retrieving text using chunking, embedding, and vector search techniques. It provides an easy-to-use interface for saving, searching, and managing textual data with associated metadata and is designed for use cases where low latency is essential. Vector search and embeddings are essential when working with large language models because they enable efficient and accurate retrieval of relevant information from massive datasets. ...Starting Price: Free -
28
SplineCloud
SplineCloud
...Users can also reuse datasets and relations in their models and calculations by accessing them directly through the SplineCloud API or by utilizing open source client libraries for Python and MATLAB. The platform supports the development of reusable engineering and analytical applications, aiming to reduce redundancy in design processes, preserve expert knowledge, and facilitate better decision-making. -
29
Microsoft R Open
Microsoft
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. ... -
30
CanvasJS Charts
Fenopix Technologies
...Graphs support various interactive features like tooltips, zooming, panning, animation, events, drill-down, exporting and can easily be integrated with various server-side technologies like PHP, Ruby, Python, ASP.Net, Node.JS, Java, etc. To top it all off, it can easily render thousands of data points without any performance lag. CanvasJS supports 30 different types of Charts and renders across devices including iPhone, iPad, Android, Mac & PCs. This allows you to create rich dashboards that work across devices without compromising on maintainability or functionality of your web application.
