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Deep Learning Software
Deep learning software provides tools and frameworks for developing, training, and deploying artificial neural networks, particularly for complex tasks such as image and speech recognition, natural language processing (NLP), and autonomous systems. These platforms leverage large datasets and powerful computational resources to enable machines to learn patterns and make predictions. Popular deep learning software includes frameworks like TensorFlow, PyTorch, Keras, and Caffe, which offer pre-built models, libraries, and tools for designing custom models. Deep learning software is essential for industries that require advanced AI solutions, including healthcare, finance, automotive, and entertainment.
Machine Learning Software
Machine learning software enables developers and data scientists to build, train, and deploy models that can learn from data and make predictions or decisions without being explicitly programmed. These tools provide frameworks and algorithms for tasks such as classification, regression, clustering, and natural language processing. They often come with features like data preprocessing, model evaluation, and hyperparameter tuning, which help optimize the performance of machine learning models. With the ability to analyze large datasets and uncover patterns, machine learning software is widely used in industries like healthcare, finance, marketing, and autonomous systems. Overall, this software empowers organizations to leverage data for smarter decision-making and automation.
Language Learning Software
Language learning software offers structured programs designed to teach users new languages through interactive lessons and exercises. These platforms typically include modules for grammar, vocabulary, pronunciation, and listening comprehension, helping learners build foundational language skills. Many language learning software options utilize multimedia tools, such as audio, video, and quizzes, to reinforce lessons and keep users engaged. Some software also offers tracking features to monitor progress and set personalized learning goals. With the flexibility to learn at one's own pace, these tools make it possible to study languages from beginner to advanced levels, often providing support for multiple languages.
Online Learning Platforms
Online learning platforms enable users to learn about a wide variety of topics. Online learning platforms, sometimes known as MOOCs (Massive Open Online Courses) or EdTech platforms, allow anyone to learn new topics and skills. Online learning platforms can be used by individuals, or by companies and organizations that want to educate and upskill their employees.
Learning Management Systems (LMS)
A Learning Management System, or LMS, is a software platform used to create, deliver and manage online training programs. They provide instructors with the ability to design course content, track learner progress, assess performance and generate reports. Learners also benefit from self-paced learning options that are available through most systems. Additionally, an LMS can be tailored to meet specific organizational needs such as providing specialized learning paths for different job roles.
Mobile Learning Software
Mobile learning software enables learners to access educational content and training materials on mobile devices, such as smartphones and tablets, enhancing flexibility and accessibility. These platforms typically offer features like interactive lessons, quizzes, progress tracking, and multimedia content that can be accessed anytime, anywhere. Mobile learning software is widely used for both formal education and corporate training, providing users with a more engaging, personalized learning experience. By using this software, businesses and educational institutions can deliver content to learners on-the-go, increase engagement, and improve knowledge retention.
Learning Experience Platforms
Learning Experience Platforms (LXPs) are advanced digital platforms designed to deliver personalized, engaging, and learner-centric education and training experiences. They aggregate content from various sources—such as courses, videos, articles, and social learning—and use AI to recommend relevant learning paths based on individual needs and preferences. LXPs support interactive features like social collaboration, gamification, and assessments to boost learner motivation and retention. By integrating with Learning Management Systems (LMS) and other HR tools, they provide seamless tracking and analytics of learning progress. Ultimately, LXPs empower organizations to foster continuous skill development and adapt learning to the evolving needs of employees and learners.
Learning Analytics Software
Learning analytics software enables organizations to collect, measure, and analyze learning data from learning management systems, training software, and educational software.
Social Learning Platforms
Social learning platforms are online tools that facilitate the exchange of knowledge and information between individuals. These platforms enable users to connect with others who share similar interests or goals, allowing them to engage in meaningful discussions and collaborative learning activities. They often offer a variety of features such as discussion forums, virtual classrooms, and interactive content to enhance the learning experience. Users can also track their progress and receive feedback from peers and instructors on these platforms. Overall, social learning platforms provide a convenient and accessible way for individuals to learn new skills and expand their knowledge through interaction with others.
Active Learning Software
Active learning tools in artificial intelligence are systems designed to enhance the efficiency of machine learning by strategically selecting the most valuable data points for training.
eLearning Content Providers
eLearning content providers create and deliver educational materials and courses in digital formats, making learning accessible online. They offer a wide range of content, from professional training and certifications to academic subjects and personal development. These providers often use multimedia elements—such as videos, quizzes, and interactive exercises—to enhance engagement and understanding. With scalable platforms, eLearning content providers cater to diverse audiences, including corporations, educational institutions, and individual learners. Their goal is to make quality education flexible and accessible, supporting learning anywhere, anytime.
Machine Learning as a Service Software
Machine Learning as a Service (MLaaS) platforms provide users with cloud-based access to pre-trained models and algorithms for predictive analytics and data analysis. MLaaS makes machine learning accessible by eliminating the need to develop and maintain complex infrastructure, instead allowing users to leverage remote computing resources in order to generate insights quickly and easily. These platforms vary in terms of features, services and pricing, offering different combinations designed to cater to a range of user needs.
AI Language Learning Software
AI language learning apps use artificial intelligence to help users learn new languages more efficiently by personalizing the learning experience. These apps often offer interactive lessons, voice recognition, and real-time feedback to improve pronunciation, grammar, and vocabulary. The AI algorithms adapt to the user's learning pace, strengths, and weaknesses, providing tailored exercises and challenges.
Neural Network Software
Neural network software uses algorithms to simulate the human brain's ability to recognize patterns. It can be used for a variety of purposes, such as image and voice recognition, natural language processing, and decision making. The software is typically composed of a number of layers that contain parameters which are adjusted through training. Finally, it can be applied in various areas such as healthcare, finance, engineering and more.
eLearning Authoring Tools
eLearning authoring tools are software platforms that enable educators, instructional designers, and businesses to create interactive and engaging online learning content. These tools allow users to design courses, lessons, quizzes, and assessments without needing extensive programming knowledge. Features typically include drag-and-drop functionality, multimedia integration (text, images, videos, audio), and SCORM or xAPI compatibility for integration with Learning Management Systems (LMS). Some eLearning authoring tools also support responsive design, enabling content to be viewed on various devices like desktops, tablets, and smartphones. They are commonly used to develop courses for corporate training, academic programs, and professional development.
Corporate Learning Management Systems Software
Corporate learning management systems (LMS) are software platforms that help companies manage, track and deliver employee training. They provide a centralized repository for all the educational resources a company makes available, as well as tracking and reporting tools to measure progress. An LMS can also be used to create customized individual learning plans or onboarding experiences.
Healthcare Learning Management Systems (LMS)
Healthcare learning management systems (LMS) are digital platforms used to help healthcare organizations improve their education and training processes. They provide features such as course and content authoring, user tracking and reporting, mobile device accessibility and more. With these tools, healthcare providers can optimize their training methods for better patient outcomes.
Hospitality Learning Management Systems (LMS) Software
Hospitality Learning Management Systems (LMS) provide a comprehensive solution to the challenges of staff training and compliance in the hospitality industry.
Learning Content Management Systems (LCMS) Software
A learning content management system (LCMS) is a software application designed to facilitate the creation, organization, and delivery of educational materials. It allows users to upload, organize, and manage course content such as videos, documents, and interactive quizzes.
AI-Based Learning Management Systems Software
AI-based learning management systems (LMS) leverage artificial intelligence to enhance the educational experience by personalizing learning paths for each student. These systems use algorithms to analyze learners' progress and adapt content, making recommendations based on individual strengths, weaknesses, and preferences. AI-powered LMS can automate administrative tasks, such as grading and feedback, allowing instructors to focus more on interaction and engagement. Additionally, they provide real-time analytics, offering insights into student performance, engagement levels, and overall learning trends.
View more categories (20) for "deep learning with python"

35 Products for "deep learning with python" with 4 filters applied:

  • 1
    Ray

    Ray

    Anyscale

    Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. ...
    Starting Price: Free
  • 2
    Qloo

    Qloo

    Qloo

    Qloo is the “Cultural AI”, decoding and predicting consumer taste across the globe. A privacy-first API that predicts global consumer preferences and catalogs hundreds of millions of cultural entities. Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things. Our technology empowers you to look beyond trends and uncover the connections behind people’s tastes in the world...
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  • 3
    Teradata VantageCloud
    ...Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems.
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  • 4
    Chalk

    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
  • 5
    Google Cloud Speech-to-Text
    ...Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device.
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    Starting Price: Free ($300 in free credits)
  • 6
    Xilinx

    Xilinx

    Xilinx

    ...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.
  • 7
    Vertex AI
    Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex...
    Starting Price: Free ($300 in free credits)
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  • 8
    Keepsake

    Keepsake

    Replicate

    Keepsake is an open-source Python library designed to provide version control for machine learning experiments and models. It enables users to automatically track code, hyperparameters, training data, model weights, metrics, and Python dependencies, ensuring that all aspects of the machine learning workflow are recorded and reproducible. Keepsake integrates seamlessly with existing workflows by requiring minimal code additions, allowing users to continue training as usual while Keepsake saves code and weights to Amazon S3 or Google Cloud Storage. ...
    Starting Price: Free
  • 9
    Towhee

    Towhee

    Towhee

    You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your...
    Starting Price: Free
  • 10
    Deep Block

    Deep Block

    Omnis Labs

    Deep Block is the world's fastest AI-powered remote sensing imagery analysis solution. Train your own AI models to detect instantly any objects in large satellite, aerial, and drone images. Deep Block's no-code data labeling interface lets you achieve your MLOps projects in days, with no prior expertise. Instead of hiring your own in-house AI engineering team, anybody can start training their own AI. If you have a mouse and a keyboard, you can use our web-based platform, check our...
    Starting Price: $10 per month
  • 11
    Deep Talk

    Deep Talk

    Deep Talk

    Deep Talk is the fastest way to transform text from chats, emails, surveys, reviews, social networks into real business intelligence. Understand what's inside communications with customers with our easy-to-use AI platform. Unsupervised deep learning models to analyze your unstructured text data. Deepers are pre trained deep learning models to get custom detections inside your data.
    Starting Price: $90 per month
  • 12
    Pathway

    Pathway

    Pathway

    Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and...
  • 13
    RunPod

    RunPod

    RunPod

    RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. ...
    Starting Price: $0.40 per hour
  • 14
    Fraud.net

    Fraud.net

    Fraud.net, Inc.

    Fraudnet's AI-driven platform empowers enterprises to prevent threats, streamline compliance, and manage risk in real-time. Our sophisticated machine learning models continuously learn from billions of transactions to identify anomalies and predict fraud attacks. Our unified solutions: comprehensive screening for smoother onboarding & improved compliance, continuous monitoring to proactively identify new threats, & precision fraud detection across channels and payment types. With dozens...
  • 15
    Deep Infra

    Deep Infra

    Deep Infra

    Powerful, self-serve machine learning platform where you can turn models into scalable APIs in just a few clicks. Sign up for Deep Infra account using GitHub or log in using GitHub. Choose among hundreds of the most popular ML models. Use a simple rest API to call your model. Deploy models to production faster and cheaper with our serverless GPUs than developing the infrastructure yourself.
    Starting Price: $0.70 per 1M input tokens
  • 16
    Key Ward

    Key Ward

    Key Ward

    ...Automatically centralize, update, extract, sort, clean, and prepare your multi-source data for analysis, machine learning, and/or deep learning. Use our advanced analytics tools on your experimental & simulation data to correlate, find dependencies, and identify patterns.
    Starting Price: €9,000 per year
  • 17
    UnionML

    UnionML

    Union

    Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning.
  • 18
    MLlib

    MLlib

    Apache Software Foundation

    ​Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. ...
  • 19
    Oracle Machine Learning
    Machine learning uncovers hidden patterns and insights in enterprise data, generating new value for the business. Oracle Machine Learning accelerates the creation and deployment of machine learning models for data scientists using reduced data movement, AutoML technology, and simplified deployment. Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology.
  • 20
    Vaex

    Vaex

    Vaex

    At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data...
  • 21
    MLflow

    MLflow

    MLflow

    ...MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. ...
  • 22
    Predibase

    Predibase

    Predibase

    ...Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want.
  • 23
    SAS Visual Machine Learning
    Access, manipulate, analyze and present information in visual formats using a powerful combination of SAS technologies. With SAS Visual Machine Learning, you can broaden your analytics with machine learning and deep learning capabilities that are accessible across your organization for better visualization and reporting. Visualize and discover relevant relationships in your data. Create and share interactive reports and dashboards, and use self-service analytics to quickly assess probable outcomes for smarter, more data-driven decisions. ...
  • 24
    Aporia

    Aporia

    Aporia

    Create customized monitors for your machine learning models with our magically-simple monitor builder, and get alerts for issues like concept drift, model performance degradation, bias and more. Aporia integrates seamlessly with any ML infrastructure. Whether it’s a FastAPI server on top of Kubernetes, an open-source deployment tool like MLFlow or a machine learning platform like AWS Sagemaker.
  • 25
    Comet

    Comet

    Comet

    Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for...
    Starting Price: $179 per user per month
  • 26
    Ensemble Dark Matter
    Train accurate ML models on limited, sparse, and high-dimensional data without extensive feature engineering by creating statistically optimized representations of your data. By learning how to extract and represent complex relationships in your existing data, Dark Matter improves model performance and speeds up training without extensive feature engineering or resource-intensive deep learning, enabling data scientists to spend less time on data and more time-solving hard problems. Dark Matter significantly improved model precision and f1 scores in predicting customer conversion in the online retail space. ...
  • 27
    Domino Enterprise MLOps Platform
    The Domino platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams...
  • 28
    Lambda

    Lambda

    Lambda

    Lambda provides high-performance supercomputing infrastructure built specifically for training and deploying advanced AI systems at massive scale. Its Superintelligence Cloud integrates high-density power, liquid cooling, and state-of-the-art NVIDIA GPUs to deliver peak performance for demanding AI workloads. Teams can spin up individual GPU instances, deploy production-ready clusters, or operate full superclusters designed for secure, single-tenant use. Lambda’s architecture emphasizes...
  • 29
    Descartes Labs

    Descartes Labs

    Descartes Labs

    ...Data science teams can use our scaling infrastructure to design models faster than ever, using our massive data archive or their own. Customers rely on our cloud-based platform to quickly and securely scale computer vision, statistical, and machine learning models to inform business decisions with powerful raster-based analytics. Our extensive API documentation, tutorials, guides and demos provide a deep knowledge base for users allowing them to quickly deploy high-value applications across diverse industries.
  • 30
    IBM Watson Studio
    ...Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. 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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