Best AI Development Platforms for Windows of 2024

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

Runlve is at the forefront of the AI revolution. We provide data science, MLOps and data & models management to empower our community and customers with AI capabilities that will propel their projects forward.

Cloobot X, a Next Gen No-Code Platform for Enterprises with in-house IT Teams, offers the following value proposition: Overcome the limitations of existing No Code Platforms (Scalability and Vendor Lock-In, etc.) 2. Support problem solvers such as consultants, domain experts and product managers at all stages of the Software Development Lifecycle. Instantly deliverables such as Prototypes (in a programming language you choose), MVPs (in a chosen programming language), Workflow Apps and Codebases (in whichever programming languages you choose) can reduce the time to delivery 10x. 4. Enable Enterprises adapt Gen AI and address concerns (Platform can run on custom LLMs; code is generated using proprietary algorithm, not by Code-based LLMs).

TorchScript allows you to seamlessly switch between graph and eager modes. TorchServe accelerates the path to production. The torch-distributed backend allows for distributed training and performance optimization in production and research. PyTorch is supported by a rich ecosystem of libraries and tools that supports NLP, computer vision, and other areas. PyTorch is well-supported on major cloud platforms, allowing for frictionless development and easy scaling. Select your preferences, then run the install command. Stable is the most current supported and tested version of PyTorch. This version should be compatible with many users. Preview is available for those who want the latest, but not fully tested, and supported 1.10 builds that are generated every night. Please ensure you have met the prerequisites, such as numpy, depending on which package manager you use. Anaconda is our preferred package manager, as it installs all dependencies.

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

CORE is a high performance computing platform that can be used for a variety of applications. CORE is easy to use with its point-and-click interface. You can run the most complex applications. CORE provides unlimited computing power on-demand. Cloud computing is available without the high-cost. CORE for teams offers powerful tools that allow you to sort, filter, create, connect, and create users, machines, networks, and machines. With an intuitive and simple GUI, it's easier than ever to see all of your infrastructure from one place. It is easy to add Active Directory integration or VPN through our simple but powerful management console. It's now possible to do things that used to take days, or even weeks. Even complex network configurations can be managed with just a few clicks.

Your ML model can be served in minutes in any cloud. Unified model packaging format that allows online and offline delivery on any platform. Our micro-batching technology allows for 100x more throughput than a regular flask-based server model server. High-quality prediction services that can speak the DevOps language, and seamlessly integrate with common infrastructure tools. Unified format for deployment. High-performance model serving. Best practices in DevOps are incorporated. The service uses the TensorFlow framework and the BERT model to predict the sentiment of movie reviews. DevOps-free BentoML workflow. This includes deployment automation, prediction service registry, and endpoint monitoring. All this is done automatically for your team. This is a solid foundation for serious ML workloads in production. Keep your team's models, deployments and changes visible. You can also control access via SSO and RBAC, client authentication and auditing logs.

Infrastructure to build, run, and manage autonomous agents Open-source AI framework that allows you to quickly and reliably develop and deploy useful agents.

Exspanse simplifies the path between development and business value. Build, train and rapidly deploy powerful machine-learning models using a single interface that scales with your business. Exspanse Notebook allows you to train, tune and prototype models with the help from high-powered GPUs, processors & AI code assistant. Rapid deploy allows you to go beyond training and modeling by deploying models as APIs directly from an Exspanse Notebook. Clone and publish unique AI project to DeepSpace AI Marketplace to advance the AI Community. Power, efficiency and collaboration all in one platform. You can maximize your impact as a data scientist working alone. Our integrated platform allows you to manage and accelerate the AI development process. Turn your innovative ideas quickly and efficiently into working models. You can seamlessly transition from building AI solutions to deploying them, without needing extensive DevOps expertise.

DeepSpeed is a deep learning optimization library that is open source for PyTorch. It is designed to reduce memory and computing power, and to train large distributed model with better parallelism using existing computer hardware. DeepSpeed is optimized to provide high throughput and low latency training. DeepSpeed can train DL-models with more than 100 billion parameters using the current generation GPU clusters. It can also train as many as 13 billion parameters on a single GPU. DeepSpeed, developed by Microsoft, aims to provide distributed training for large models. It's built using PyTorch which is a data parallelism specialist.

Even the most complex requests from users can be fulfilled by our advanced planning engine. Out-of-the-box automation, inside your product. Your users can ask the system to do amazing things by using simple text, such as "Please show me sales from last month and give me some suggestions". OpenCopilot can be integrated into your product by using our chat bubble. No coding knowledge is required. You can also use our SDKs for your copilot to blend in. You can also feed all kinds of data to your copilot and it will be capable of understanding it and offering help to your users. OpenCopilot can be hosted on your own website with a simple make install command. All paid plans come with personal support from our team. Your users can ask complicated questions that require multiple actions to be executed in one go. The single platform for building, managing, and deploying your next AI-powered features. You will be the first to get new features, which is great since we ship so much.

AlwaysAI offers developers a simple and flexible way for them to create, train, and deploy computer-vision applications to a wide range of IoT devices. You can choose from a variety of deep learning models, or upload your own. Our flexible and customizable APIs make it easy to quickly enable core computer vision services. You can quickly prototype, test, and iterate using a variety camera-enabled ARM32, ARM64, and x86 devices. Identify objects in an image using their names or classifications. Identify and count objects in real-time video feeds. Follow the same object through a series of frames. To count or track faces or complete bodies in a scene, locate them. Identify and draw borders around objects. You can separate the key objects from the background visuals in an image. Determine human body postures, fall detection, and emotions. To train an object detection model, use our model training toolkit. You can create a model that is tailored to your particular use-case.

The hybrid front-end seamlessly switches between Gluon eager symbolic mode and Gluon imperative mode, providing flexibility and speed. The dual parameter server and Horovod support enable scaleable distributed training and performance optimization for research and production. Deep integration into Python, support for Scala and Julia, Clojure and Java, C++ and R. MXNet is supported by a wide range of tools and libraries that allow for use-cases in NLP, computer vision, time series, and other areas. Apache MXNet is an Apache Software Foundation (ASF) initiative currently incubating. It is sponsored by the Apache Incubator. All accepted projects must be incubated until further review determines that infrastructure, communications, decision-making, and decision-making processes have stabilized in a way consistent with other successful ASF projects. Join the MXNet scientific network to share, learn, and receive answers to your questions.

The Intel Distribution of OpenVINO makes it easy to adopt and maintain your code. Open Model Zoo offers optimized, pre-trained models. Model Optimizer API parameters make conversions easier and prepare them for inferencing. The runtime (inference engines) allows you tune for performance by compiling an optimized network and managing inference operations across specific devices. It auto-optimizes by device discovery, load balancencing, inferencing parallelism across CPU and GPU, and many other functions. You can deploy the same application to multiple host processors and accelerators (CPUs. GPUs. VPUs.) and environments (on-premise or in the browser).

RapidCanvas is a no-code AI platform that helps businesses go from idea to live AI solution within hours. Our AutoAI technology automates the AI build and deploy process, reducing time to value by 90% or more. We work with you to understand your needs and create out-of-the-box AI solutions that are tailored to your specific business requirements. Our data science experts are available to help you optimize the results and ensure that you are satisfied with the performance of your AI solution. RapidCanvas is used by leaders in the Financial Services, Retail, Renewable Energy, and Manufacturing industries. We are committed to helping businesses of all sizes get the most out of AI.

Open Agent Studio is more than just another copilot. It's a co-pilot builder with no code that allows solutions that are not possible in any other RPA tool today. We believe that other tools will copy our idea, and so we are giving our customers a head start in the next few months. They can target markets previously untapped by AI using their deep industry insights. Subscribers can access a 4-week free course that teaches them how to evaluate product concepts and launch a customized agent with a white label enterprise-grade. You can easily build agents by recording your keyboard and mice actions, such as scraping data and detecting a start node. The agent recorder allows you to build generalized agents in as little time as possible. Record once and then share it across your organization for future-proof agents.