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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"
50 Products for "python regex" with 2 filters applied:
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1
Tinybird
Tinybird
Query and shape your data using Pipes, a new way to chain SQL queries inspired by Python Notebooks. Designed to reduce complexity without sacrificing performance. By splitting your query in different nodes you simplify development and maintenance. Activate your production-ready API endpoints with one click. Transformations occur on-the-fly so you will always work with the latest data. Share access securely to your data in one click and get fast and consistent results.Starting Price: $0.07 per processed GB -
2
DQOps
DQOps
...DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.Starting Price: $499 per month -
3
Chalk
Chalk
Powerful data engineering workflows, without the infrastructure headaches. Complex streaming, scheduling, and data backfill pipelines, are all defined in simple, composable Python. Make ETL a thing of the past, fetch all of your data in real-time, no matter how complex. Incorporate deep learning and LLMs into decisions alongside structured business data. Make better predictions with fresher data, don’t pay vendors to pre-fetch data you don’t use, and query data just in time for online predictions. Experiment in Jupyter, then deploy to production. ...Starting Price: Free -
4
ScrapFly
ScrapFly
...The Extraction API utilizes AI and large language models to parse documents and extract structured data, while the screenshot API allows for capturing high-quality visuals of web pages. These tools are built to scale, ensuring reliability and performance as data needs grow. Scrapfly also provides comprehensive documentation, SDKs in Python and TypeScript, and integrations with platforms like Zapier and Make to facilitate seamless integration into various workflows.Starting Price: $30 per month -
5
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 -
6
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 -
7
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 -
8
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 -
9
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 -
10
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. ... -
11
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 -
12
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 -
13
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. -
14
...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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15
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 -
16
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. -
17
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 -
18
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. ... -
19
DataClarity Unlimited Analytics
DataClarity
.... | REAL-TIME ANALYSIS – Perform advanced analysis & data exploration using drill-down, drill-through, filters, built-in statistical & predictive models, or your own Python and R code. | SEAMLESS APPLICATION INTEGRATION – Achieve smooth integration with versatile APIs, tailor-made configurations & flexible embedding features. | SECURITY & GOVERNANCE – Ensure adherence to your security guidelines, governance standards, multitenancy, row-level data protection, and Single Sign-On (SSO).Starting Price: FREE -
20
Redis
Redis Labs
...Implement relational databases, active-active, geo-distribution, built in conflict distribution for simple and complex data types, & reads/writes in multiple geo regions to the same data set. Redis Enterprise offers flexible deployment options, cloud on-prem, & hybrid. Redis Labs: home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.Starting Price: Free
