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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
Megaladata
Megaladata
...The platform supports both self-service and enterprise-grade systems, handling big data with high performance. IT has integrations with more then 50 of the main databases' software and online datasets, other then native compatibility with Micrsoft ecosystem and Python. Available as a desktop, server, or cloud solution, Megaladata is used across industries like banking, retail, logistics, and healthcare. Free, interactive training online courses help users solve real business problems efficiently.Starting Price: Free, Community Edition -
2
ScraperX
ScraperX
ScraperX is an AI-powered web scraping API designed to simplify and accelerate data extraction from any website. It offers intuitive integration with support for multiple programming languages, including Node.js, Python, Java, Go, C#, Perl, PHP, and Visual Basic. It features smart data extraction that automatically identifies and captures relevant data patterns across various website structures, eliminating the need for manual configuration. Users can send API requests specifying the website and data to extract, and the platform processes and analyzes the data accordingly. ...Starting Price: $40 per month -
3
ZeusDB
ZeusDB
...The platform delivers ultra-low latency querying and real-time analytics, eliminating the need for separate databases or caching layers. Developers and data engineers can extend functionality with Rust or Python logic, deploy on-premises, hybrid, or cloud, and operate under GitOps/CI-CD patterns with observability built in. With built-in vector indexing (e.g., HNSW), metadata filtering, and powerful query semantics, ZeusDB enables similarity search, hybrid retrieval, filtering, and rapid application iteration. -
4
RStudio
Posit
RStudio IDE is a powerful integrated development environment built for data scientists using R and Python; it features a console, syntax-highlighting editor supporting direct code execution, plotting, history management, debugging tools, and workspace controls. The open source edition runs on Windows, Mac, and Linux desktops and includes code completion, smart indentation, Visual Markdown editing, project-based working directories, integrated support for multiple working directories, R help and documentation search, interactive debugging, and extensive tools for package development, all under the AGPL v3 license. ...Starting Price: $1,163 per year -
5
Nixtla
Nixtla
...It was trained on over 100 billion data points spanning domains such as retail, energy, finance, IoT, healthcare, weather, web traffic, and more, allowing it to make accurate zero-shot predictions across a wide variety of use cases. With just a few lines of code (e.g., via their Python SDK), users can supply historical data and immediately generate forecasts or detect anomalies, even for irregular or sparse time series, and without needing to build or train models from scratch. TimeGPT supports advanced features like handling exogenous variables (e.g., events, prices), forecasting multiple time-series at once, custom loss functions, cross-validation, prediction intervals, and model fine-tuning on bespoke datasets.Starting Price: Free -
6
Parallel Domain Replica Sim
Parallel Domain
...With PD Replica, you can generate near-pixel-perfect reconstructions of real-world scenes, transforming them into virtual environments that preserve visual detail and realism. PD Sim provides a Python API through which perception, machine learning, and autonomy teams can configure and run large-scale test scenarios and simulate sensor inputs (camera, lidar, radar, etc.) in either open- or closed-loop mode. These simulated sensor feeds come with full annotations, so developers can test their perception systems under a wide variety of conditions, lighting, weather, object configurations, and edge cases, without needing to collect real-world data for every scenario. -
7
MonetDB
MonetDB
...When you're curious about what's in your data; when you want to work efficiently; when your deadline is closing: MonetDB returns query result in mere seconds or even less. When you want to (re)use your own code; when you need specialised functions: use the hooks to add your own user-defined functions in SQL, Python, R or C/C++. Join us and expand the MonetDB community spread over 130+ countries with students, teachers, researchers, start-ups, small businesses and multinational enterprises. Join the leading Database in Analytical Jobs and surf the innovation! Don’t lose time with complex installation, use MonetDB’s easy setup to get your DBMS up and running quickly. -
8
Hopsworks
Logical Clocks
Hopsworks is an open-source Enterprise platform for the development and operation of Machine Learning (ML) pipelines at scale, based around the industry’s first Feature Store for ML. You can easily progress from data exploration and model development in Python using Jupyter notebooks and conda to running production quality end-to-end ML pipelines, without having to learn how to manage a Kubernetes cluster. Hopsworks can ingest data from the datasources you use. Whether they are in the cloud, on‑premise, IoT networks, or from your Industry 4.0-solution. Deploy on‑premises on your own hardware or at your preferred cloud provider. ...Starting Price: $1 per month -
9
Apache Spark
Apache Software Foundation
...Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. ... -
10
Apache Ignite
Apache Ignite
Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and order your distributed in-memory and on-disk data. Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases. Think of a cache that you can query with SQL, transact, and compute on. ... -
11
Ascend
Ascend
...Backed by DataAware intelligence, Ascend works continuously in the background to guarantee data integrity and optimize data workloads, reducing time spent on maintenance by up to 90%. Build, iterate on, and run data transformations easily with Ascend’s multi-language flex-code interface enabling the use of SQL, Python, Java, and, Scala interchangeably. Quickly view data lineage, data profiles, job and user logs, system health, and other critical workload metrics at a glance. Ascend delivers native connections to a growing library of common data sources with our Flex-Code data connectors.Starting Price: $0.98 per DFC -
12
Zepl
Zepl
...Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. ... -
13
Amazon SageMaker JumpStart
Amazon
...SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs, including TensorFlow Hub, PyTorch Hub, HuggingFace, and MxNet GluonCV. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis. -
14
Datorios
Datorios
...Visualize changes pre-deployment to ease dev processes, expedite testing, and simplify debugging. Foster team collaboration and save time on the most painful development stages by working with Python and our easy-to-use interface. Consolidate any amount of data, in any format and from endless sources with zero data storing processing hesitations. Guarantee the most accurate data with error flagging and real-time debugging within specific data processes and across pipelines in their entirety. Utilize compute, storage, and network bandwidth to efficiently auto-scale your infrastructure as data volume and velocity increase. ...Starting Price: Free -
15
ScrapingBypass
ScrapingBypass
...Includes interface address, request parameters, return processing. Also allows setting of Referrer, browser UA, headless status, and other browser fingerprint device features. Support: Python, Curl, Java, NodeJS Bypass CAPTCHA Verification Code Available to CAPTCHA, GeeTest and other verification codes Bypass Cloudflare Verification Bypass Cloudflare anti-bot scraping shield WAF, CC protection Unlimited Data Scraping Built-in one-stop global exclusive high hidden static proxy IPStarting Price: $5.9/3 days -
16
kdb Insights
KX
...With supreme scalability, kdb Insights handles extensive real-time and historical data, proven at volumes of up to 110 terabytes per day. Its quick setup and simple data intake accelerate time-to-value, while native support for q, SQL, and Python, along with compatibility with other languages via RESTful APIs. -
17
Hyperbrowser
Hyperbrowser
...The platform supports over 10,000 concurrent browsers with sub-millisecond latency, ensuring scalable and reliable browsing with a 99.9% uptime guarantee. Hyperbrowser is compatible with various tech stacks, including Python and Node.js, and provides both synchronous and asynchronous clients for seamless integration.Starting Price: $30 per month -
18
Browser Use
Browser Use
Browser Use is an open source Python library that enables AI agents to interact seamlessly with web browsers. Combining advanced AI capabilities with robust browser automation allows AI agents to perform tasks such as applying for jobs, visiting links, extracting information, and answering messages on platforms like WhatsApp. The library supports multiple large language models, including GPT-4, Claude 3, and Llama 2, facilitating complex web operations through a simple interface. ... -
19
mydataprovider
mydataprovider
Do you want to develop a python web scraper or maybe a javascript web scraper? Are you looking for a web scraping service? You found! We provide Web scraping service since 2009. We can scrape any website for you. Our core expertise is web scraping and we can scrape any type of site. Max web scraping speed we got is 17000 web requests/minute from 1 server with a 100MB/s network. -
20
...OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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21
GeoSpock
GeoSpock
...Users are able to perform analysis and share insights using familiar toolsets, with support for common BI tools (such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™), and Data Science and Machine Learning environments (including Python Notebooks and Apache Spark). The database can also be integrated with internal applications and web services – with compatibility for open-source and visualisation libraries such as Kepler and Cesium.js. -
22
Weights & Biases
Weights & Biases
...It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence. -
23
Deepnote
Deepnote
...Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connectionStarting Price: Free -
24
SolveXia
SolveXia
...Automated data quality checks and exception reporting. Easily store and process massive amounts of data. Embedded BI to create stunning visualisations from your data. Connectors to AI services and support for Python and R models. Replace your disconnected data silos with powerful, end-to-end automation. Create all of of your reports in minutes, allowing you to spend more time on analysis. Processes can pause, request and collect approvals and data from humans. Share processes and data with your team and reduce key-person risk. -
25
TCS MasterCraft DataPlus
Tata Consultancy Services
...Efficiently addresses growing volumes of data efficiently, through service engine-based architecture. Handles niche data processing requirements, beyond out of box functionality, through a user-defined function framework and python adapter. Provides a lean layer of governance surrounding data privacy and data quality management. -
26
Hex
Hex
Hex brings together the best of notebooks, BI, and docs into a seamless, collaborative UI. Hex is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. Your default landing page in Hex is the Projects page. You can quickly find projects you created, as well as those shared with you and your workspace. The outline provides an easy-to-browse overview of all the cells in a project's Logic View. Every cell in the outline lists the variables it defines, and cells that return a displayed output (chart cells, Input Parameters, markdown cells, etc.) display a preview of that output. ...Starting Price: $24 per user per month -
27
InterSystems Caché
InterSystems
...InterSystems Caché provides several APIs to operate with same data simultaneously: key-value, relational, object, document, multi-dimensional. Data can be managed via SQL, Java, node.js, .NET, C++, Python. Caché also provides an application server which hosts web apps (CSP), REST, SOAP, web sockets and other types of TCP access for Caché data. -
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InterSystems IRIS
InterSystems
...InterSystems IRIS provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS includes -
29
Posit
Posit
Posit builds tools that help data scientists work more efficiently, collaborate seamlessly, and share insights securely across their organizations. Its Positron code editor provides the speed of an interactive console combined with the power to build, debug, and deploy data-science workflows in Python and R. Posit’s platform enables teams to scale open-source data science, offering enterprise-ready capabilities for publishing, sharing, and operationalizing applications. Companies rely on Posit’s secure infrastructure to host Shiny apps, dashboards, APIs, and analytical reports with confidence. Whether using open-source packages or cloud-based solutions, Posit supports reproducible, high-quality work at every stage of the data lifecycle. ... -
30
...Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
