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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.
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.
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.
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.
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.
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.
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29 Products for "deep learning with python" with 2 filters applied:

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  • 1
    NVIDIA TensorRT
    NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. ...
    Starting Price: Free
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  • 2
    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.
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  • 3
    DeepCube

    DeepCube

    DeepCube

    DeepCube provides the only technology that allows efficient deployment of deep learning models on intelligent edge devices. After the deep learning training phase, the resulting model typically requires huge amounts of processing and consumes lots of memory. Due to the significant amount of memory and processing requirements, today’s deep learning deployments are limited mostly to the cloud.
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  • 4
    Exafunction

    Exafunction

    Exafunction

    Exafunction optimizes your deep learning inference workload, delivering up to a 10x improvement in resource utilization and cost. Focus on building your deep learning application, not on managing clusters and fine-tuning performance. In most deep learning applications, CPU, I/O, and network bottlenecks lead to poor utilization of GPU hardware. Exafunction moves any GPU code to highly utilized remote resources, even spot instances.
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  • 5
    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...
    743 Ratings
    Starting Price: Free ($300 in free credits)
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  • 6
    IBM Watson Machine Learning Accelerator
    Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. ...
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  • 7
    NetApp AIPod
    NetApp AIPod is a comprehensive AI infrastructure solution designed to streamline the deployment and management of artificial intelligence workloads. By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and...
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  • 8
    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
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  • 9
    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. ...
    180 Ratings
    Starting Price: $0.40 per hour
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  • 10
    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.
    1 Rating
    Starting Price: $0.70 per 1M input tokens
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  • 11
    Zebra by Mipsology
    Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application.
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  • 12
    Qualcomm Cloud AI SDK
    The Qualcomm Cloud AI SDK is a comprehensive software suite designed to optimize trained deep learning models for high-performance inference on Qualcomm Cloud AI 100 accelerators. It supports a wide range of AI frameworks, including TensorFlow, PyTorch, and ONNX, enabling developers to compile, optimize, and execute models efficiently. The SDK provides tools for model onboarding, tuning, and deployment, facilitating end-to-end workflows from model preparation to production deployment. ...
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  • 13
    Luminal

    Luminal

    Luminal

    Luminal is a machine-learning framework built for speed, simplicity, and composability, focusing on static graphs and compiler-based optimization to deliver high performance even for complex neural networks. It compiles models into minimal “primops” (only 12 primitive operations) and then applies compiler passes to replace those with device-specific optimized kernels, enabling efficient execution on GPU or other backends. It supports modules (building blocks of networks with a standard...
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  • 14
    AWS Inferentia
    AWS Inferentia accelerators are designed by AWS to deliver high performance at the lowest cost for your deep learning (DL) inference applications. The first-generation AWS Inferentia accelerator powers Amazon Elastic Compute Cloud (Amazon EC2) Inf1 instances, which deliver up to 2.3x higher throughput and up to 70% lower cost per inference than comparable GPU-based Amazon EC2 instances. Many customers, including Airbnb, Snap, Sprinklr, Money Forward, and Amazon Alexa, have adopted Inf1 instances and realized its performance and cost benefits. ...
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  • 15
    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. ...
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  • 16
    AWS Neuron

    AWS Neuron

    Amazon Web Services

    It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal...
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  • 17
    Google Cloud AI Infrastructure
    Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. ...
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  • 18
    MaiaOS

    MaiaOS

    Zyphra Technologies

    ...We have deep expertise across AI models, learning algorithms, and systems/infrastructure with a focus on inference efficiency and AI silicon performance. Zyphra's team is committed to democratizing advanced AI systems.
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  • 19
    ONNX

    ONNX

    ONNX

    ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. Develop in your preferred framework without worrying about downstream inferencing implications. ONNX enables you to use your preferred framework with your chosen inference engine.
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  • 20
    Amazon EC2 G5 Instances
    Amazon EC2 G5 instances are the latest generation of NVIDIA GPU-based instances that can be used for a wide range of graphics-intensive and machine-learning use cases. They deliver up to 3x better performance for graphics-intensive applications and machine learning inference and up to 3.3x higher performance for machine learning training compared to Amazon EC2 G4dn instances. Customers can use G5 instances for graphics-intensive applications such as remote workstations, video rendering, and...
    Starting Price: $1.006 per hour
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  • 21
    NVIDIA DGX Cloud
    NVIDIA DGX Cloud offers a fully managed, end-to-end AI platform that leverages the power of NVIDIA’s advanced hardware and cloud computing services. This platform allows businesses and organizations to scale AI workloads seamlessly, providing tools for machine learning, deep learning, and high-performance computing (HPC). DGX Cloud integrates seamlessly with leading cloud providers, delivering the performance and flexibility required to handle the most demanding AI applications. This service is ideal for businesses looking to enhance their AI capabilities without the need to manage physical infrastructure.
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  • 22
    Valohai

    Valohai

    Valohai

    Models are temporary, pipelines are forever. Train, Evaluate, Deploy, Repeat. Valohai is the only MLOps platform that automates everything from data extraction to model deployment. Automate everything from data extraction to model deployment. Store every single model, experiment and artifact automatically. Deploy and monitor models in a managed Kubernetes cluster. Point to your code & data and hit run. Valohai launches workers, runs your experiments and shuts down the instances for you....
    Starting Price: $560 per month
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  • 23
    NVIDIA Run:ai
    NVIDIA Run:ai is an enterprise platform designed to optimize AI workloads and orchestrate GPU resources efficiently. It dynamically allocates and manages GPU compute across hybrid, multi-cloud, and on-premises environments, maximizing utilization and scaling AI training and inference. The platform offers centralized AI infrastructure management, enabling seamless resource pooling and workload distribution. Built with an API-first approach, Run:ai integrates with major AI frameworks and...
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  • 24
    NVIDIA NIM
    ...NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. ...
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  • 25
    NeuReality

    NeuReality

    NeuReality

    NeuReality accelerates the possibilities of AI by offering a revolutionary solution that lowers the overall complexity, cost, and power consumption. While other companies also develop Deep Learning Accelerators (DLAs) for deployment, no other company connects the dots with a software platform purpose-built to help manage specific hardware infrastructure. NeuReality is the only company that bridges the gap between the infrastructure where AI inference runs and the MLOps ecosystem. NeuReality has developed a new architecture design to exploit the power of DLAs. ...
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  • 26
    ThirdAI

    ThirdAI

    ThirdAI

    ...ThirdAI accelerator builds hash-based processing algorithms for training and inference with neural networks. The technology is a result of 10 years of innovation in finding efficient (beyond tensor) mathematics for deep learning. Our algorithmic innovation has demonstrated how we can make Commodity x86 CPUs 15x or faster than most potent NVIDIA GPUs for training large neural networks. The demonstration has shaken the common knowledge prevailing in the AI community that specialized processors like GPUs are significantly superior to CPUs for training neural networks. ...
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  • 27
    Stochastic

    Stochastic

    Stochastic

    ...Our goal was to show that it is possible to achieve impressive results in financial NLP tasks without breaking the bank. Personal AI assistant, your own AI to chat with your documents. Single or multiple documents, easy or complex questions, and much more. Effortless deep learning platform for enterprises, hardware efficient algorithms to speed up inference at a lower cost. Real-time logging and monitoring of resource utilization and cloud costs of deployed models. xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application.
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  • 28
    Clarifai

    Clarifai

    Clarifai

    Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for developing better, faster and stronger AI. We help our customers create innovative solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. The platform comes with the broadest repository of pre-trained,...
    Starting Price: $0
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  • 29
    Together AI

    Together AI

    Together AI

    ...Together AI delivers industry-leading cost efficiency by optimizing hardware, scheduling, and inference techniques, lowering total cost of ownership for demanding AI workloads. With deep research expertise, the company brings cutting-edge models, hardware, and runtime innovations—like ATLAS runtime-learning accelerators—directly into production environments. Its full-stack ecosystem includes a model library, inference APIs, fine-tuning capabilities, pre-training support, and instant GPU clusters. Designed for AI-native teams, Together AI helps organizations build and deploy advanced applications faster and more affordably.
    Starting Price: $0.0001 per 1k tokens
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