Best Machine Learning Software - Page 9
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Compare the Top Machine Learning Software as of August 2025 - Page 9
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1
Kaggle
Kaggle
Kaggle offers a no-setup, customizable, Jupyter Notebooks environment. Access free GPUs and a huge repository of community published data & code. Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 public datasets and 200,000 public notebooks to conquer any analysis in no time. -
2
Cloud Dataprep
Google
Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis, reporting, and machine learning. Because Cloud Dataprep is serverless and works at any scale, there is no infrastructure to deploy or manage. Your next ideal data transformation is suggested and predicted with each UI input, so you don’t have to write code. Cloud Dataprep is an integrated partner service operated by Trifacta and based on their industry-leading data preparation solution. Google works closely with Trifacta to provide a seamless user experience that removes the need for up-front software installation, separate licensing costs, or ongoing operational overhead. Cloud Dataprep is fully managed and scales on demand to meet your growing data preparation needs so you can stay focused on analysis. -
3
Amazon Augmented AI (A2I)
Amazon
Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers. Many machine learning applications require humans to review low confidence predictions to ensure the results are correct. For example, extracting information from scanned mortgage application forms can require human review in some cases due to low-quality scans or poor handwriting. But building human review systems can be time consuming and expensive because it involves implementing complex processes or “workflows”, writing custom software to manage review tasks and results, and in many cases, managing large groups of reviewers. -
4
Appen
Appen
The Appen platform combines human intelligence from over one million people all over the world with cutting-edge models to create the highest-quality training data for your ML projects. Upload your data to our platform and we provide the annotations, judgments, and labels you need to create accurate ground truth for your models. High-quality data annotation is key for training any AI/ML model successfully. After all, this is how your model learns what judgments it should be making. Our platform combines human intelligence at scale with cutting-edge models to annotate all sorts of raw data, from text, to video, to images, to audio, to create the accurate ground truth needed for your models. Create and launch data annotation jobs easily through our plug and play graphical user interface, or programmatically through our API. -
5
Dataloop AI
Dataloop AI
Manage unstructured data and pipelines to develop AI solutions at amazing speed. Enterprise-grade data platform for vision AI. Dataloop is a one-stop shop for building and deploying powerful computer vision pipelines data labeling, automating data ops, customizing production pipelines and weaving the human-in-the-loop for data validation. Our vision is to make machine learning-based systems accessible, affordable and scalable for all. Explore and analyze vast quantities of unstructured data from diverse sources. Rely on automated preprocessing and embeddings to identify similarities and find the data you need. Curate, version, clean, and route your data to wherever it’s needed to create exceptional AI applications. -
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Sixgill Sense
Sixgill
Every step of the machine learning and computer vision workflow is made simple and fast within one no-code platform. Sense allows anyone to build and deploy AI IoT solutions to any cloud, the edge or on-premise. Learn how Sense provides simplicity, consistency and transparency to AI/ML teams with enough power and depth for ML engineers yet easy enough to use for subject matter experts. Sense Data Annotation optimizes the success of your machine learning models with the fastest, easiest way to label video and image data for high-quality training dataset creation. The Sense platform offers one-touch labeling integration for continuous machine learning at the edge for simplified management of all your AI solutions. -
7
Swivl
Education Bot, Inc
swivl is simplifying AI training. In general, data scientists typically spend 80% of their time on non-value-added tasks such as finding, cleaning, and annotating data. Our no-code SaaS platform helps teams outsource these data annotation tasks to a vetted network of data annotators to close the feedback loop in a cost-effective way. This involves the action of training, testing, and deploying machine learning models with an emphasis on natural language processing, audio, and generalized data categorization.Starting Price: $149/mo/user -
8
Kraken
Big Squid
Kraken is for everyone from analysts to data scientists. Built to be the easiest-to-use, no-code automated machine learning platform. The Kraken no-code automated machine learning (AutoML) platform simplifies and automates data science tasks like data prep, data cleaning, algorithm selection, model training, and model deployment. Kraken was built with analysts and engineers in mind. If you've done data analysis before, you're ready! Kraken's no-code, easy-to-use interface and integrated SONAR© training make it easy to become a citizen data scientist. Advanced features allow data scientists to work faster and more efficiently. Whether you use Excel or flat files for day-to-day reporting or just ad-hoc analysis and exports, drag-and-drop CSV upload and the Amazon S3 connector in Kraken make it easy to start building models with a few clicks. Data Connectors in Kraken allow you to connect to your favorite data warehouse, business intelligence tools, and cloud storage.Starting Price: $100 per month -
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SensiML Analytics Studio
SensiML
Sensiml analytics toolkit. Create smart iot sensor devices rapidly reduce data science complexity. Create compact algorithms that execute on tiny IoT endpoints, not in the cloud. Collect accurate, traceable, version controlled datasets. Utilize advanced AutoML code-gen to quickly produce autonomous working device code. Choose your interface, level of AI expertise, and retain full access to every aspect of your algorithm. Build edge tuning models that that customize behavior as they see more data. SensiML Analytics Toolkit suite automates each step of the process for creating optimized AI IoT sensor recognition code. The overall workflow uses a growing library of advanced ML and AI algorithms to generate code that can learn from new data either the development phase or once deployed. Non-invasive, rapid disease screening applications utilizing intelligent classification of one or more bio-sensing inputs are critical tools for healthcare decision support. -
10
Intellimize
Intellimize
With your marketing ideas and our machine learning, you can optimize your web site for every single visitor. Simultaneously test all of your most creative marketing ideas to constantly showcase the messaging, content, and experiences that performs best. This is way beyond A/B testing and old-school, rules-based personalization. This is the new standard for high-converting landing pages across your website. This is Continuous Conversion™—and it changes… everything. -
11
Weights & Biases
Weights & Biases
Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence. -
12
TiMi
TIMi
With TIMi, companies can capitalize on their corporate data to develop new ideas and make critical business decisions faster and easier than ever before. The heart of TIMi’s Integrated Platform. TIMi’s ultimate real-time AUTO-ML engine. 3D VR segmentation and visualization. Unlimited self service business Intelligence. TIMi is several orders of magnitude faster than any other solution to do the 2 most important analytical tasks: the handling of datasets (data cleaning, feature engineering, creation of KPIs) and predictive modeling. TIMi is an “ethical solution”: no “lock-in” situation, just excellence. We guarantee you a work in all serenity and without unexpected extra costs. Thanks to an original & unique software infrastructure, TIMi is optimized to offer you the greatest flexibility for the exploration phase and the highest reliability during the production phase. TIMi is the ultimate “playground” that allows your analysts to test the craziest ideas! -
13
Privacera
Privacera
At the intersection of data governance, privacy, and security, Privacera’s unified data access governance platform maximizes the value of data by providing secure data access control and governance across hybrid- and multi-cloud environments. The hybrid platform centralizes access and natively enforces policies across multiple cloud services—AWS, Azure, Google Cloud, Databricks, Snowflake, Starburst and more—to democratize trusted data enterprise-wide without compromising compliance with regulations such as GDPR, CCPA, LGPD, or HIPAA. Trusted by Fortune 500 customers across finance, insurance, retail, healthcare, media, public and the federal sector, Privacera is the industry’s leading data access governance platform that delivers unmatched scalability, elasticity, and performance. Headquartered in Fremont, California, Privacera was founded in 2016 to manage cloud data privacy and security by the creators of Apache Ranger™ and Apache Atlas™. -
14
Innotescus
Innotescus
Innotescus is a collaborative video and image annotation platform built to streamline Computer Vision development processes via seamless data handling, smart annotation tools, and intuitive collaboration features. Additionally, its data visualization tools and cross-functional collaboration features identify data bias early, improve data accuracy, and enable faster, cost-efficient deployment of high performance Artificial Intelligence. -
15
MLflow
MLflow
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. 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. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects. -
16
Altair Knowledge Studio
Altair
Data scientists and business analysts use Altair to generate actionable insight from their data. Knowledge Studio is a market-leading easy to use machine learning and predictive analytics solution that rapidly visualizes data as it quickly generates explainable results - without requiring a single line of code. A recognized analytics leader, Knowledge Studio brings transparency and automation to machine learning with features such as AutoML and explainable AI without restricting how models are configured and tuned, giving you control over model building. Knowledge Studio is designed to enable collaboration across the business. Data scientists and business analysts can complete complex projects in minutes or hours, not weeks or months. Results are easily understood and explained. The ease of use and automation of steps of the modeling process enable data scientists to efficiently develop more machine learning models faster than coding or using other tools. -
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Altair Knowledge Works
Altair
It is undeniable that data and analytics are key drivers behind transformative business initiatives. More people across the enterprise are accessing data to answer complex questions. The demand for easy-to-use, low-code yet flexible data transformation and machine learning tools has never been greater. The use of multiple tools leads to inefficient data analytic processes, higher costs, and slows down decision making. Aging solutions with overlapping features threaten current data science projects as proprietary functions in closed vendor solutions become obsolete. Combining decades of experience in data preparation, machine learning and visualization with one unified interface Knowledge Works scales as data sizes grow, new open source features and functionalities are developed, and user profiles become more sophisticated. Data scientists and business analysts can efficiently operationalize data analytics applications using its low-code, cloud ready interface. -
18
ML Kit
Google
ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package. Make your iOS and Android apps more engaging, personalized, and helpful with solutions that are optimized to run on device. ML Kit’s processing happens on-device. This makes it fast and unlocks real-time use cases like processing of camera input. It also works while offline and can be used for processing images and text that need to remain on the device. Take advantage of the machine learning technologies that power Google's own experiences on mobile. We combine best-in-class machine learning models with advanced processing pipelines and offer these through easy-to-use APIs to enable powerful use cases in your apps. Recognizes handwritten text and handdrawn shapes on a digital surface, such as a touch screen. Recognizes 300+ languages, emojis and basic shapes. -
19
Oracle Data Science
Oracle
A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results. -
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Xilinx
Xilinx
The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! 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. -
21
Kepler
Stradigi AI
Leverage Kepler’s Automated Data Science Workflows and remove the need for coding and machine learning experience. Onboard quickly and generate data-driven insights unique to your organization and your data. Receive continuous updates & additional Workflows built by our world-class AI and ML team via our SaaS-based model. Scale AI and accelerate time-to-value with a platform that grows with your business using the team and skills already present within your organization. Address complex business problems with advanced AI and machine learning capabilities without the need for technical ML experience. Leverage state-of-the-art, end-to-end automation, an extensive library of AI algorithms, and the ability to quickly deploy machine learning models. Organizations are using Kepler to augment and automate critical business processes to improve productivity and agility. -
22
IceCream Labs
IceCream Labs
We help our clients leverage visual AI to solve real-world business problems. Our team of skilled data scientists and machine learning engineers will quickly train and deliver highly precise and accurate machine learning models for your visual data. IceCream Labs is the leading enterprise AI solution company. IceCream Labs provides solutions for retail, digital media and higher education. The company’s expertise is developing machine learning and deep learning models to solve real world business problems using text, image and numerical data. Try IceCream Labs if your business handles visual data like images, video and documents. If you need to identify what’s in an image or a document, we can help you. If you need to quickly train and deploy a machine learning model, IceCream Labs is the answer. Talk to our AI experts and get sales performance improvements across your product line. -
23
Alfi
Alfi
Alfi, Inc. engages in creating interactive digital out-of-home advertising experiences. Alfi utilizes artificial intelligence and computer vision to better serve ads to people. Alfi’s proprietary Ai algorithm understands small facial cues and perceptual details that make potential customers a good candidate for a particular product. The automation works in a way that respects user privacy; without tracking, storing cookies, or using identifiable personal information. Ad agencies are empowered to examine real-time analytics data including interactive experiences, engagement, sentiment, and click-through rate that are otherwise unavailable to out-of-home advertisers. Alfi, powered by AI and machine learning, collects data to understand human behavior for improved analytics with relevant content for a better consumer experience. -
24
Neural Magic
Neural Magic
GPUs bring data in and out quickly, but have little locality of reference because of their small caches. They are geared towards applying a lot of compute to little data, not little compute to a lot of data. The networks designed to run on them therefore execute full layer after full layer in order to saturate their computational pipeline (see Figure 1 below). In order to deal with large models, given their small memory size (tens of gigabytes), GPUs are grouped together and models are distributed across them, creating a complex and painful software stack, complicated by the need to deal with many levels of communication and synchronization among separate machines. CPUs, on the other hand, have large, much faster caches than GPUs, and have an abundance of memory (terabytes). A typical CPU server can have memory equivalent to tens or even hundreds of GPUs. CPUs are perfect for a brain-like ML world in which parts of an extremely large network are executed piecemeal, as needed. -
25
TruEra
TruEra
A machine learning monitoring solution that helps you easily oversee and troubleshoot high model volumes. With explainability accuracy that’s unparalleled and unique analyses that are not available anywhere else, data scientists avoid false alarms and dead ends, addressing critical problems quickly and effectively. Your machine learning models stay optimized, so that your business is optimized. TruEra’s solution is based on an explainability engine that, due to years of dedicated research and development, is significantly more accurate than current tools. TruEra’s enterprise-class AI explainability technology is without peer. The core diagnostic engine is based on six years of research at Carnegie Mellon University and dramatically outperforms competitors. The platform quickly performs sophisticated sensitivity analysis that enables data scientists, business users, and risk and compliance teams to understand exactly how and why a model makes predictions. -
26
Gretel
Gretel.ai
Privacy engineering tools delivered to you as APIs. Synthesize and transform data in minutes. Build trust with your users and community. Gretel’s APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy. Keeping the pace with development velocity requires faster access to data. Gretel is accelerating access to data with data privacy tools that bypass blockers and fuel Machine Learning and AI applications. Keep your data contained by running Gretel containers in your own environment or scale out workloads to the cloud in seconds with Gretel Cloud runners. Using our cloud GPUs makes it radically more effortless for developers to train and generate synthetic data. Scale workloads automatically with no infrastructure to set up and manage. Invite team members to collaborate on cloud projects and share data across teams. -
27
Rasgo
Rasgo
Rasgo brings the power of GPT-4 to enterprise data analytics with its advanced platform, allowing businesses to leverage AI-driven insights directly from their enterprise data warehouses (EDWs). The platform securely integrates with existing data systems to automate the extraction and interpretation of meaningful insights, reducing the need for manual data manipulation. Rasgo’s AI agents use natural language to interact with data, uncover valuable trends, and deliver continuous, proactive insights, empowering teams to make data-informed decisions and driving operational efficiency 24/7. -
28
Torch
Torch
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner. -
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SHARK
SHARK
SHARK is a fast, modular, feature-rich open-source C++ machine learning library. It provides methods for linear and nonlinear optimization, kernel-based learning algorithms, neural networks, and various other machine learning techniques. It serves as a powerful toolbox for real-world applications as well as research. Shark depends on Boost and CMake. It is compatible with Windows, Solaris, MacOS X, and Linux. Shark is licensed under the permissive GNU Lesser General Public License. Shark provides an excellent trade-off between flexibility and ease-of-use on the one hand, and computational efficiency on the other. Shark offers numerous algorithms from various machine learning and computational intelligence domains in a way that they can be easily combined and extended. Shark comes with a lot of powerful algorithms that are to our best knowledge not implemented in any other library. -
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Automaton AI
Automaton AI
With Automaton AI’s ADVIT, create, manage and develop high-quality training data and DNN models all in one place. Optimize the data automatically and prepare it for each phase of the computer vision pipeline. Automate the data labeling processes and streamline data pipelines in-house. Manage the structured and unstructured video/image/text datasets in runtime and perform automatic functions that refine your data in preparation for each step of the deep learning pipeline. Upon accurate data labeling and QA, you can train your own model. DNN training needs hyperparameter tuning like batch size, learning, rate, etc. Optimize and transfer learning on trained models to increase accuracy. Post-training, take the model to production. ADVIT also does model versioning. Model development and accuracy parameters can be tracked in run-time. Increase the model accuracy with a pre-trained DNN model for auto-labeling.
