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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.
Financial Data APIs Software
Financial data APIs software enable the interaction with financial applications in order to access transaction and payment information.
Finance Software
Financial software is a broad category of financial software. Finance software provides all the necessary tools to record, store, manage, analyze and process financial information, accounting, trading, records, bills, transactions, and more.
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.
Code Search Engines
Code search engines are specialized search tools that allow developers to search through codebases, repositories, or libraries to find specific functions, variables, classes, or code snippets. These tools are designed to help developers quickly locate relevant parts of code, analyze code quality, and identify reusable components. Code search engines often support various programming languages, providing search capabilities like syntax highlighting, filtering by file types or attributes, and even advanced search options using regular expressions. They are particularly useful for navigating large codebases, enhancing code reuse, and improving overall productivity in software development projects.
View more categories (6) for "python tkinter"
  • 1
    QuantRocket

    QuantRocket

    QuantRocket

    QuantRocket is a Python-based platform for researching, backtesting, and trading quantitative strategies. It provides a JupyterLab environment, offers a suite of data integrations, and supports multiple backtesters: Zipline, the open-source backtester that originally powered Quantopian; Alphalens, an alpha factor analysis library; Moonshot, a vectorized backtester based on pandas; and MoonshotML, a walk-forward machine learning backtester. Built on Docker, QuantRocket can be deployed locally...
  • 2
    Barchart OnDemand
    ..., JSON and CSV, and can be streamed over WebSockets. We’re compatible with any operating system, such as Windows, Linux, iOS or Android, and any programming language, such as Python, Java, PHP, R, or ASP.NET. We embrace the cloud but also maintain physical data centers for specific client needs. Through our Equinix-based facilities we cater to low latency requirements and provide a true physical back-up.
  • 3
    Quandl

    Quandl

    Quandl

    The premier source for financial, economic, and alternative datasets, serving investment professionals. Quandl’s platform is used by over 400,000 people, including analysts from the world’s top hedge funds, asset managers and investment banks. Quandl delivers market data from hundreds of sources via API, or directly into Python, R, Excel and many other tools. Save time and money by getting the data you need in the format you want. Our unparalleled consumption experience frees your analysts...
  • 4
    SolveXia

    SolveXia

    SolveXia

    ... 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.
  • 5
    Commoditic

    Commoditic

    Commoditic

    ... API are also available in several other programming languages like Javascript, JQuery, VueJS, Angular, JAVA, PHP, NodeJS, Python, Go, Ruby, C#, R, Strest, Rust, Swift and Scala. Regardless of the data delivery method users choose, they access commodity pricing data right away. Commoditic has customers of diverse background. We help fintechs, financial institutions, investors, traders, universities and freelance developers streamline their projects.
    Starting Price: $79
  • 6
    Ntropy

    Ntropy

    Ntropy

    Ship faster integrating with our Python SDK or Rest API in minutes. No prior setups or data formatting. You can get going straight away as soon as you have incoming data and your first customers. We have built and fine-tuned custom language models to recognize entities, automatically crawl the web in real-time and pick the best match, as well as assign labels with superhuman accuracy in a fraction of the time. Everybody has a data enrichment model that is trying to be good at one thing, US...
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