Best Machine Learning Software for Mac of 2025

Fraud.net is the world's leading infrastructure for fraud management. It is powered by a sophisticated collective Intelligence network, world-class AI, and a modern cloud-based platform that assists you: * Combine fraud data from all sources with one connection * Detect fraudulent activity in real-time for transactions exceeding 99.5% * Uncover hidden insights in Terabytes of data to optimize fraud management Fraud.net was recognized in Gartner's market guide for online fraud detection. It is a real-time enterprise-strength, enterprise-strength, fraud prevention and analytics solution that is tailored to the needs of its business customers. It acts as a single point-of-command, combining data from different sources and systems, tracking digital identities and behaviors, then deploying the most recent tools and technologies to eradicate fraudulent activity and allow transactions to go through. Get a free trial by contacting us today

TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.

Mixpanel's mission is to increase innovation. Mixpanel is not only a company but also a service provider for businesses. Companies can use our engagement and analytics product to analyze how users interact, convert, retain, and engage with them in real-time on web, mobile, or smart devices. They can then use this data to improve their products and business. Mixpanel serves more than 26,000 companies in different industries worldwide, including Samsung, Twitter and BMW. Mixpanel is headquartered in San Francisco and has offices in New York City, Seattle, Austin. London, Paris, Barcelona, Paris, London, and Singapore.

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

Neural Designer is a data-science and machine learning platform that allows you to build, train, deploy, and maintain neural network models. This tool was created to allow innovative companies and research centres to focus on their applications, not on programming algorithms or programming techniques. Neural Designer does not require you to code or create block diagrams. Instead, the interface guides users through a series of clearly defined steps. Machine Learning can be applied in different industries. These are some examples of machine learning solutions: - In engineering: Performance optimization, quality improvement and fault detection - In banking, insurance: churn prevention and customer targeting. - In healthcare: medical diagnosis, prognosis and activity recognition, microarray analysis and drug design. Neural Designer's strength is its ability to intuitively build predictive models and perform complex operations.

Herbie.ai is a multi-national Conversational AI company. (Part of SunSmart Global, 15+ years in enterprise solutions). Digital Transformation of Enterprises Virtual Assistants with Voice Enabled to Automate Business Cases Franchise expanded to 6 countries. Instant connects you with 12+ social media platforms.

Ametnes: A Streamlined Data App Deployment Management Ametnes is the future of data applications deployment. Our cutting-edge solution will revolutionize the way you manage data applications in your private environments. Manual deployment is a complex process that can be a security concern. Ametnes tackles these challenges by automating the whole process. This ensures a seamless, secure experience for valued customers. Our intuitive platform makes it easy to deploy and manage data applications. Ametnes unlocks the full potential of any private environment. Enjoy efficiency, security and simplicity in a way you've never experienced before. Elevate your data management game - choose Ametnes today!

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.

Smart Software, a leading provider in demand planning, inventory optimization, and supply chain analytics solutions, is based in Belmont, Massachusetts USA. Smart Software was founded in 1981 and has helped thousands of customers plan for future demands using industry-leading statistical analysis. Smart Inventory Planning & Optimization is the company's next generation suite of native web apps. It helps inventory-carrying organizations reduce inventory, improve service levels, and streamline Sales, Inventory, Operations Planning. Smart IP&O is a Digital Supply Chain Platform that hosts three applications: dashboard reporting, inventory optimization, demand planning. Smart IP&O acts as an extension to our customers' ERP systems. It receives daily transaction data, returns forecasts and stock policy values to drive replenishment planning and production planning.

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 building better, faster and stronger AI. We help enterprises and public sector organizations transform their data into actionable insights. Our technology is used across many industries including Defense, Retail, Manufacturing, Media and Entertainment, and more. We help our customers create innovative AI solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been a market leader in computer vision AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai is headquartered in Delaware

NaturalText A.I. Your data can be used to get more. Discover relationships, build collections, and uncover hidden insights in documents and text-based data. NaturalText A.I. NaturalText A.I. uses artificial intelligence technology to uncover hidden data relationships. The software uses a variety of state-of-the art methods to understand context and analyze patterns to reveal insights - all in a human-readable manner. Discover hidden insights in your data It can be difficult, if not impossible, to find everything in your text data. Traditional search can only find information about a document. NaturalText A.I. on the other hand, uncovers new data within millions of documents, including patents and scientific papers. NaturalText A.I. NaturalText A.I. can help you uncover insights in your data that you are not currently seeing.

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.

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

Dagster is the cloud-native open-source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. It is the platform of choice data teams responsible for the development, production, and observation of data assets. With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early.

Ginger Software is a productivity-focused company with an award winning record. It helps you write faster and more effectively thanks to grammar checker and punctuation tools. These tools automatically detect and correct grammar mistakes and misused words. Ginger, an AI-powered writing assistant, can correct your texts, improve style, and increase your creativity. Ginger does more than just spellcheck and grammar. Ginger can suggest context-based corrections by taking into account complete sentences. This greatly speeds up writing, especially when you are working on lengthy emails or documents. Ginger's AI will suggest other ways to convey your message. It is especially useful for simplifying long sentences. To find the perfect match, double-click any word on any website.

Revolutionary machine teaching is here with an exceptionally efficient annotation tool driven by active learning. Prodigy serves as a customizable annotation platform so effective that data scientists can handle the annotation process themselves, paving the way for rapid iteration. The advancements in today's transfer learning technologies allow for the training of high-quality models using minimal examples. By utilizing Prodigy, you can fully leverage contemporary machine learning techniques, embracing a more flexible method for data gathering. This will enable you to accelerate your workflow, gain greater autonomy, and deliver significantly more successful projects. Prodigy merges cutting-edge insights from the realms of machine learning and user experience design. Its ongoing active learning framework ensures that you only need to annotate those examples the model is uncertain about. The web application is not only powerful and extensible but also adheres to the latest user experience standards. The brilliance lies in its straightforward design: it encourages you to concentrate on one decision at a time, keeping you actively engaged – akin to a swipe-right approach for data. Additionally, this streamlined process fosters a more enjoyable and effective annotation experience overall.

TADA by MyDataModels offers a top-tier predictive analytics solution that enables professionals to leverage their Small Data for business improvement through a user-friendly and easily deployable tool. With TADA, users can quickly develop predictive models that deliver actionable insights in a fraction of the time, transforming what once took days into mere hours thanks to an automated data preparation process that reduces time by 40%. This platform empowers individuals to extract valuable outcomes from their data without the need for programming expertise or advanced machine learning knowledge. By utilizing intuitive and transparent models composed of straightforward formulas, users can efficiently optimize their time and turn raw data into meaningful insights effortlessly across various platforms. The complexity of predictive model construction is significantly diminished as TADA automates the generative machine learning process, making it as simple as inputting data to receive a model output. Moreover, TADA allows for the creation and execution of machine learning models on a wide range of devices and platforms, ensuring accessibility through its robust web-based pre-processing capabilities, thereby enhancing operational efficiency and decision-making.

MindsDB is the only AGI data solution that connects and unifies petabyte scale enterprise data, enabling enterprise-wide informed decision-making in real-time.

Discover a fresh library or dataset while working in a notebook environment. Streamline your preprocessing, training, or testing processes through an automated workflow. Transform your application into a functioning product by deploying it effectively. You have the flexibility to utilize notebooks, workflows, and deployments either together or on their own. Gradient is fully compatible with all major frameworks and libraries, ensuring seamless integration. Powered by Paperspace's exceptional GPU instances, Gradient allows you to accelerate your projects significantly. Enhance your development speed with integrated source control, connecting effortlessly to GitHub to oversee all your work and computing resources. Launch a GPU-enabled Jupyter Notebook right from your browser in mere seconds, using any library or framework of your choice. It's simple to invite collaborators or share a public link for your projects. This straightforward cloud workspace operates on free GPUs, allowing you to get started almost instantly with an easy-to-navigate notebook environment that's perfect for machine learning developers. Offering a robust and hassle-free setup with numerous features, it just works. Choose from pre-existing templates or integrate your own unique configurations, and take advantage of a free GPU to kickstart your projects!

KServe is a robust model inference platform on Kubernetes that emphasizes high scalability and adherence to standards, making it ideal for trusted AI applications. This platform is tailored for scenarios requiring significant scalability and delivers a consistent and efficient inference protocol compatible with various machine learning frameworks. It supports contemporary serverless inference workloads, equipped with autoscaling features that can even scale to zero when utilizing GPU resources. Through the innovative ModelMesh architecture, KServe ensures exceptional scalability, optimized density packing, and smart routing capabilities. Moreover, it offers straightforward and modular deployment options for machine learning in production, encompassing prediction, pre/post-processing, monitoring, and explainability. Advanced deployment strategies, including canary rollouts, experimentation, ensembles, and transformers, can also be implemented. ModelMesh plays a crucial role by dynamically managing the loading and unloading of AI models in memory, achieving a balance between user responsiveness and the computational demands placed on resources. This flexibility allows organizations to adapt their ML serving strategies to meet changing needs efficiently.

The NVIDIA Triton™ inference server provides efficient and scalable AI solutions for production environments. This open-source software simplifies the process of AI inference, allowing teams to deploy trained models from various frameworks, such as TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, and more, across any infrastructure that relies on GPUs or CPUs, whether in the cloud, data center, or at the edge. By enabling concurrent model execution on GPUs, Triton enhances throughput and resource utilization, while also supporting inferencing on both x86 and ARM architectures. It comes equipped with advanced features such as dynamic batching, model analysis, ensemble modeling, and audio streaming capabilities. Additionally, Triton is designed to integrate seamlessly with Kubernetes, facilitating orchestration and scaling, while providing Prometheus metrics for effective monitoring and supporting live updates to models. This software is compatible with all major public cloud machine learning platforms and managed Kubernetes services, making it an essential tool for standardizing model deployment in production settings. Ultimately, Triton empowers developers to achieve high-performance inference while simplifying the overall deployment process.

Flyte is a robust platform designed for automating intricate, mission-critical data and machine learning workflows at scale. It simplifies the creation of concurrent, scalable, and maintainable workflows, making it an essential tool for data processing and machine learning applications. Companies like Lyft, Spotify, and Freenome have adopted Flyte for their production needs. At Lyft, Flyte has been a cornerstone for model training and data processes for more than four years, establishing itself as the go-to platform for various teams including pricing, locations, ETA, mapping, and autonomous vehicles. Notably, Flyte oversees more than 10,000 unique workflows at Lyft alone, culminating in over 1,000,000 executions each month, along with 20 million tasks and 40 million container instances. Its reliability has been proven in high-demand environments such as those at Lyft and Spotify, among others. As an entirely open-source initiative licensed under Apache 2.0 and backed by the Linux Foundation, it is governed by a committee representing multiple industries. Although YAML configurations can introduce complexity and potential errors in machine learning and data workflows, Flyte aims to alleviate these challenges effectively. This makes Flyte not only a powerful tool but also a user-friendly option for teams looking to streamline their data operations.

OpenCV, which stands for Open Source Computer Vision Library, is a freely available software library designed for computer vision and machine learning. Its primary goal is to offer a unified framework for developing computer vision applications and to enhance the integration of machine perception in commercial products. As a BSD-licensed library, OpenCV allows companies to easily adapt and modify its code to suit their needs. It boasts over 2500 optimized algorithms encompassing a wide array of both traditional and cutting-edge techniques in computer vision and machine learning. These powerful algorithms enable functionalities such as facial detection and recognition, object identification, human action classification in videos, camera movement tracking, and monitoring of moving objects. Additionally, OpenCV supports the extraction of 3D models, creation of 3D point clouds from stereo camera input, image stitching for high-resolution scene capture, similarity searches within image databases, red-eye removal from flash photographs, and even eye movement tracking and landscape recognition, showcasing its versatility in various applications. The extensive capabilities of OpenCV make it a valuable resource for developers and researchers alike.

Giskard provides interfaces to AI & Business teams for evaluating and testing ML models using automated tests and collaborative feedback. Giskard accelerates teamwork to validate ML model validation and gives you peace-of-mind to eliminate biases, drift, or regression before deploying ML models into production.