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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.
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.
Artificial Intelligence Software
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics.
AI Development Platforms
AI development platforms are tools that enable developers to build, manage, and deploy AI applications. These platforms provide the necessary infrastructure for the development of AI models, such as access to data sets and computing resources. They can also help facilitate the integration of data sources or be used to create workflows for managing machine learning algorithms. Finally, these platforms provide an environment for deploying models into production systems so they can be used by end users.
View more categories (6) for "python prolog"
  • 1
    SuperAGI SuperCoder
    SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experience
    Starting Price: Free
  • 2
    Steamship

    Steamship

    Steamship

    ...Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. ...
  • 3
    Sieve

    Sieve

    Sieve

    ...Package models with a simple Python decorator and deploy them instantly. A full-featured observability stack so you have full visibility of what’s happening under the hood. Pay only for what you use, by the second. Gain full control over your costs.
    Starting Price: $20 per month
  • 4
    Semantic Kernel
    ...Version 1.0+ support across C#, Python, and Java means it’s reliable, and committed to nonbreaking changes. Any existing chat-based APIs are easily expanded to support additional modalities like voice and video. Semantic Kernel was designed to be future-proof, easily connecting your code to the latest AI models evolving with the technology as it advances.
    Starting Price: Free
  • 5
    DataChain

    DataChain

    iterative.ai

    DataChain connects unstructured data in cloud storage with AI models and APIs, enabling instant data insights by leveraging foundational models and API calls to quickly understand your unstructured files in storage. Its Pythonic stack accelerates development tenfold by switching to Python-based data wrangling without SQL data islands. DataChain ensures dataset versioning, guaranteeing traceability and full reproducibility for every dataset to streamline team collaboration and ensure data integrity. It allows you to analyze your data where it lives, keeping raw data in storage (S3, GCP, Azure, or local) while storing metadata in inefficient data warehouses. ...
    Starting Price: Free
  • 6
    MakerSuite
    ...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.
  • 7
    Anyscale

    Anyscale

    Anyscale

    Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. ...
    Starting Price: $0.00006 per minute
  • 8
    Gradio

    Gradio

    Gradio

    ...Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share.
  • 9
    Instructor

    Instructor

    Instructor

    Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of validators and custom error messages, enhancing data validation processes. ...
    Starting Price: Free
  • 10
    Chainlit

    Chainlit

    Chainlit

    Chainlit is an open-source Python package designed to expedite the development of production-ready conversational AI applications. With Chainlit, developers can build and deploy chat-based interfaces in minutes, not weeks. The platform offers seamless integration with popular AI tools and frameworks, including OpenAI, LangChain, and LlamaIndex, allowing for versatile application development.
  • 11
    Encord

    Encord

    Encord

    ...Expert review, QA and QC workflows help you deliver higher quality datasets to your artificial intelligence teams, helping improve model performance. Connect your data and models with Encord's Python SDK and API access to create automated pipelines for continuously training ML models. Improve model accuracy by identifying errors and biases in your data, labels and models.
  • 12
    Prompt flow

    Prompt flow

    Microsoft

    ...It makes prompt engineering much easier and enables you to build LLM apps with production quality. With Prompt Flow, you can create flows that link LLMs, prompts, Python code, and other tools together in an executable workflow. It allows for debugging and iteration of flows, especially tracing interactions with LLMs with ease. You can evaluate your flows, calculate quality and performance metrics with larger datasets, and integrate the testing and evaluation into your CI/CD system to ensure quality. ...
  • 13
    Interlify

    Interlify

    Interlify

    ...It offers flexible API management, enabling you to add or remove APIs for LLM access with simple clicks through its management console, customizing your setup based on your project's evolving needs without hassle. Additionally, Interlify provides a lightning-fast client setup, allowing integration into your project with just a few lines of code in Python or TypeScript, saving valuable time and effort.
    Starting Price: $19 per month
  • 14
    Arcade

    Arcade

    Arcade

    ...By acting as an authenticated proxy based on the OpenAI API spec, Arcade.dev lets models invoke external services (such as Gmail, Slack, GitHub, Salesforce, Notion, and more) via pre-built connectors or custom tool SDKs, managing authentication, token handling, and security seamlessly. Developers work with a unified client interface (arcadepy for Python or arcadejs for JavaScript), facilitating tool execution and authorization without burdening application logic with credentials or API specifics. It supports secure deployments in the cloud, private VPCs, or on premises, and includes a control plane for managing tools, users, permissions, and observability.
    Starting Price: $50 per month
  • 15
    MXNet

    MXNet

    The Apache Software Foundation

    ...Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. ...
  • 16
    Monster API

    Monster API

    Monster API

    ...Seamless integrations with your existing systems, without the need for extensive development. Easily integrate our APIs into your workflow with support for stacks like CURL, Python, Node.js and PHP. We access the unused computing power of millions of decentralised crypto mining rigs worldwide and optimize them for machine learning and package them with popular generative AI models like Stable Diffusion. By harnessing these decentralized resources, we can provide you with a scalable, globally accessible, and, most importantly, affordable platform for Generative AI delivered through seamlessly integrable APIs.
  • 17
    SuperDuperDB

    SuperDuperDB

    SuperDuperDB

    ...Integrate and combine models from Sklearn, PyTorch, and HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Deploy all your AI models to automatically compute outputs (inference) in your datastore in a single environment with simple Python commands.
  • 18
    Zerve AI

    Zerve AI

    Zerve AI

    ...Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. ...
  • 19
    Griptape

    Griptape

    Griptape AI

    ...Griptape gives developers everything they need to build, deploy, and scale retrieval-driven AI-powered applications, from the development framework to the execution runtime. 🎢 Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. ☁️ Griptape Cloud is a one-stop shop to hosting your AI structures, whether they are built with Griptape, another framework, or call directly to the LLMs themselves. ...
    Starting Price: Free
  • 20
    Laminar

    Laminar

    Laminar

    ...All traces are sent in the background via gRPC with minimal overhead. Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. Laminar lets you go beyond a single prompt. You can build and host complex chains, including mixtures of agents or self-reflecting LLM pipelines.
    Starting Price: $25 per month
  • 21
    Lunary

    Lunary

    Lunary

    ...It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. ...
    Starting Price: $20 per month
  • 22
    Xilinx

    Xilinx

    Xilinx

    ...Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications.
  • 23
    Hyperbrowser

    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
  • 24
    OpenPipe

    OpenPipe

    OpenPipe

    ...We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. ...
    Starting Price: $1.20 per 1M tokens
  • 25
    Azure Machine Learning
    ...Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.
  • 26
    IBM Watson Studio
    ...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.
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