Alternatives to SensiML Analytics Studio
Compare SensiML Analytics Studio alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to SensiML Analytics Studio in 2026. Compare features, ratings, user reviews, pricing, and more from SensiML Analytics Studio competitors and alternatives in order to make an informed decision for your business.
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1
Google Cloud Vision AI
Google
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog. -
2
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! -
3
Oracle Machine Learning
Oracle
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. Notebooks support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression. Data scientists gain integrated model deployment from the Oracle Machine Learning AutoML User Interface. -
4
PredictSense
Winjit
PredictSense is an end-to-end Machine Learning platform powered by AutoML to create AI-powered analytical solutions. Fuel the new technological revolution of tomorrow by accelerating machine intelligence. AI is key to unlocking value from enterprise data investments. PredictSense enables businesses to monetize critical data infrastructure and technology investments by creating AI driven advanced analytical solutions rapidly. Empower data science and business teams with advanced capabilities to quickly build and deploy robust technology solutions at scale. Easily integrate AI into the current product ecosystem and fast track GTM for new AI solutions. Incur huge savings in cost, time and effort by building complex ML models in AutoML. PredictSense democratizes AI for every individual in the organization and creates a simple, user-friendly collaboration platform to seamlessly manage critical ML deployments. -
5
SquareML
SquareML
SquareML is a no-code machine learning platform designed to democratize access to advanced data analytics and predictive modeling, particularly in the healthcare sector. It enables users, regardless of technical expertise, to harness machine learning capabilities without extensive coding knowledge. The platform specializes in data ingestion from multiple sources, including electronic health records, claims databases, medical devices, and health information exchanges. Key features include a no-code data science lifecycle, generative AI models for healthcare, unstructured data conversion, diverse machine learning models for predicting patient outcomes and disease progression, a library of pre-built models and algorithms, and seamless integration with various healthcare data sources. SquareML aims to streamline data processes, enhance diagnostic accuracy, and improve patient care outcomes by providing AI-powered insights. -
6
Edge Impulse
Edge Impulse
Build advanced embedded machine learning applications without a PhD. Collect sensor, audio, or camera data directly from devices, files, or cloud integrations to build custom datasets. Leverage automatic labeling tools from object detection to audio segmentation. Set up and run reusable scripted operations that transform your input data on large sets of data in parallel by using our cloud infrastructure. Integrate custom data sources, CI/CD tools, and deployment pipelines with open APIs. Accelerate custom ML pipeline development with ready-to-use DSP and ML algorithms. Make hardware decisions based on device performance and flash/RAM every step of the way. Customize DSP feature extraction algorithms and create custom machine learning models with Keras APIs. Fine-tune your production model with visualized insights on datasets, model performance, and memory. Find the perfect balance between DSP configuration and model architecture, all budgeted against memory and latency constraints. -
7
ML.NET
Microsoft
ML.NET is a free, open source, and cross-platform machine learning framework designed for .NET developers to build custom machine learning models using C# or F# without leaving the .NET ecosystem. It supports various machine learning tasks, including classification, regression, clustering, anomaly detection, and recommendation systems. ML.NET integrates with other popular ML frameworks like TensorFlow and ONNX, enabling additional scenarios such as image classification and object detection. It offers tools like Model Builder and the ML.NET CLI, which utilize Automated Machine Learning (AutoML) to simplify the process of building, training, and deploying high-quality models. These tools automatically explore different algorithms and settings to find the best-performing model for a given scenario.Starting Price: Free -
8
Wekinator
Wekinator
The Wekinator is free, open source software. Wekinator 1.0 was originally created in 2009 by Rebecca Fiebrink. In 2015, Rebecca released Wekinator 2.0, an entirely new version with redesigned interactions, new algorithms, and ability to connect easily to dozens of other creative coding tools and sensors. Wekinator 2.0 continues to be gently updated with bug fixes and feature requests. It allows anyone to use machine learning to build new musical instruments, gestural game controllers, computer vision or computer listening systems, and more. The Wekinator allows users to build new interactive systems by demonstrating human actions and computer responses, instead of writing programming code. Create mappings between gesture and computer sounds. Control a drum machine using your webcam! Play Ableton using a Kinect! Control interactive visual environments created in Processing, OpenFrameworks, or Quartz Composer, or game engines like Unity, using gestures sensed from webcam, Kinect, etc. -
9
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 -
10
Elucid
Elucid
Deliver personalized patient care with the only histologically validated, objective, and quantitative CTA-based arterial analysis software. Utilize ground-truth histology to visualize the source of myocardial ischemia and inform heart attack and stroke risk. Heart attack and stroke are primarily caused by non-obstructive, but unstable plaque in the arteries that goes undiagnosed and untreated. Current non-invasive testing cannot visualize the biology deep inside artery walls where heart disease develops. Elucid is harnessing scientific imaging and artificial intelligence to enable quick, accurate, noninvasive diagnoses and precise treatment of cardiovascular disease to enable better patient outcomes. Assess plaque composition with histology-validated software. Quantify heart attack and stroke risk with greater accuracy. Visualize a comprehensive and objective view of arterial disease to enable personalized treatment plans before a patient ever enters the hospital. -
11
Prevision
Prevision.io
Building a model is an iterative process that can take weeks, months, or even years, and reproducing model results, maintaining version control, and auditing past work are complex. Model building is an iterative process. Ideally, you record not only each step but also how you arrived there. A model shouldn’t be a file hidden away somewhere, but instead a tangible object that all parties can track and analyze consistently. Prevision.io allows you to record each experiment as you train it along with its characteristics, automated analyses, and versions as your project progress, whether you created it using our AutoML or your own tools. Automatically experiment with dozens of feature engineering strategies and algorithm types to build highly performant models. In a single command, the engine automatically tries out different feature engineering strategies for every type of data (e.g. tabular, text, images) to maximize the information in your datasets. -
12
Oncoustics
Oncoustics
Oncoustics is creating and deploying advanced and patented AI solutions for low-cost, non-invasive surveillance, diagnostics, and treatment monitoring of diseases with high unmet clinical needs. Oncoustics offers a suite of disease and anatomy-focused apps that work on any PoC ultrasound and can be used by any MD/nurse/tech as a basic primary care office instrument, without the need to look at images. Oncoustics’ AI solutions turn the inexpensive point-of-care ultrasound devices into powerful diagnostic tools for faster, cost-effective detection and monitoring of diseases including diseases in the liver, prostate, kidney, breast, and thyroid. Our team is made up of experts in AI, signal processing, radiology, hepatology, digital health, and ultrasound. Inexpensive point of care diagnosis and surveillance improves outcomes through early detection and monitoring resulting in effective disease management. -
13
ScoopML
ScoopML
Easy-to-Use Build advanced predictive models without math & coding - in just a few clicks. Complete Experience. From cleaning data to building models to making predictions, we provide you all. Trustworthy. Know the 'why' behind AI decisions and drive business with actionable insights. Data Analytics in minutes, without writing code. The total process of building ML algorithms, explaining results, and predicting outcomes in one single click. Machine Learning in 3 Steps. Go from raw data to actionable analytics without writing a single line of code. Upload your data. Ask questions in plain english. Get the best performing model for your data and Share your results. Increase Customer Productivity. We help Companies to leverage no code Machine learning to improve their Customer Experience. -
14
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. -
15
Profet AI
Profet AI
Profet AI’s end-to-end No-Code AutoML Platform is manufacturers’ Virtual Data Scientist. It empowers industry domain/IT experts to rapidly build high-quality prediction models and deploy Industrial AI applications to solve their everyday production and digitalization challenges. Profet AI AutoML Platform is widely adopted by world's leading customers across industries, including the world's leading EMS, Semi-OSAT, PCB, IC design House, display panel and materials solution providers. We leverage industry leading companies' successful cases to benefit our customers to implement AI within one week. -
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Sensing Feeling
Sensing Feeling
Sensing Feeling offers a suite of advanced visual sensing products designed to enhance safety, efficiency, and risk management in real-world environments. SensorMAX, integrates with existing CCTV and control systems to provide real-time video analytics without recording or transmitting images, ensuring privacy. The Visual Processing Engine (VPE) operates at the edge, connecting to current Video Management Systems (VMS) or Network Video Recorders (NVR), processing feeds simultaneously. SensorMAX supports a range of algorithms for applications like crowd density monitoring, anomaly detection, and PPE compliance, and can interface with SCADA systems for automated alerts and responses. SensorCODE is tailored for embedding into low-power IoT edge systems, facilitating continuous remote sensing with real-time telemetry over networks like WiFi, LoRaWAN, and 4G/5G. -
17
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. -
18
QC Ware Forge
QC Ware
Unique and efficient turn-key algorithms for data scientists. Powerful circuit building blocks for quantum engineers. Turn-key algorithm implementations for data scientists, financial analysts, and engineers. Explore problems in binary optimization, machine learning, linear algebra, and monte carlo sampling on simulators and real quantum hardware. No prior experience with quantum computing is required. Use NISQ data loader circuits to load classical data into quantum states to use with your algorithms. Use circuit building blocks for linear algebra with distance estimation and matrix multiplication circuits. Use our circuit building blocks to create your own algorithms. Get a significant performance boost for D-Wave hardware and use the latest improvements for gate-based approaches. Try out quantum data loaders and algorithms with guaranteed speed-ups on clustering, classification, and regression.Starting Price: $2,500 per hour -
19
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. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. -
20
Apache Mahout
Apache Software Foundation
Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark. -
21
PI.EXCHANGE
PI.EXCHANGE
Easily connect your data to the engine, either through uploading a file or connecting to a database. Then, start analyzing your data through visualizations, or prepare your data for machine learning modeling with the data wrangling actions with repeatable recipes. Get the most out of your data by building machine learning models, using regression, classification or clustering algorithms - all without any code. Uncover insights into your data, using the feature importance, prediction explanation, and what-if tools. Make predictions and integrate them seamlessly into your existing systems through our connectors, ready to go so you can start taking action.Starting Price: $39 per month -
22
DragonFly IoT Active Shooter Sensors
EAGL Technology
An outdoor wireless gunshot sensor performing energy capture, waveform analysis, and transmitting resultant data to the Emergency Automatic Gunshot Detection & Lockdown (EAGL) system, a Gunshot Detection System (GDS). Compact, wireless, self-contained, battery-operated gunshot sensor executing threat versus non-threat validation analysis using energy waveform algorithms. Sensor contained within resonance chamber allowing flat wall, corner, or pole mounting capability while providing an optimum spherical detection coverage area. Threat validation data is wirelessly transmitted by sensor to the EAGL System Server via internal Quectel. Sensor data received by the EAGL System Server is processed further while initiating the appropriate pre-programmed automatic and autonomous adaptive response feature and process. Sensor also receives calibration data from the EAGL Server using similar communication processes and methods. -
23
Analance
Ducen
Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance. -
24
AtomBeam
AtomBeam
There’s no hardware to buy, no changes that need to be made to your network, and only a simple installation of a small library of software. By 2025, 75% of all enterprise-generated data, or 90 zettabytes, will be from IoT. To give a sense of scale, all of the storage capacity of every data center in the world today adds up to less than two zettabytes. Moreover, 98% of IoT data is unsecured, but all of it should be secured. Battery life for sensors is a major concern, with little relief on the horizon. Wireless data transmission range is a problem for many IoT users. We think that AtomBeam will impact IoT in the same way the electric light changed everyday living. Many key impediments to IoT adoption can be overcome with the simple addition of our compaction software. With our software alone, you can improve security, extend battery life, and increase transmission range. AtomBeam offers the opportunity for significant discounts on connectivity and cloud storage costs. -
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FireFly Indoor Gunshot Detector
EAGL Technology
The FireFly® Indoor Gunshot Detector is wireless and designed to work in Indoor environments. Installation basically entails attaching each sensor using only two fasteners. Sensor placement determines detection area coverage, unobstructed spherical range can be as much as 31,415 sqft. Compact, wireless, self-contained, battery-operated gunshot sensor executing threat versus non-threat validation analysis using energy level and waveform analysis algorithms. The sensor is mounted to horizontal ceiling substrates providing a spherical detection coverage area of ~31,415 FT2. Sensors can be attached to vertical columns presenting a decreased coverage area. Threat validation data is wirelessly transmitted by the sensor to the EAGL System Server via the EAGL Gateway. Data received by the EAGL System Server is processed further initiating the appropriate pre-programmed automatic and autonomous Adaptive Response feature and process. -
26
Folio3
Folio3 Software
Folio3 machine learning company has a team of dedicated Data Scientists and Consultants that have delivered end-to-end projects related to machine learning, natural language processing, computer vision and predictive analysis. Artificial Intelligence and Machine Learning algorithms have enabled companies to utilize highly-customized solutions equipped with advanced Machine Learning capabilities. Computer vision technology has scaled up visual data analysis, introduced new image- based functionalities and transformed the way companies from various verticals utilize visual content. Predictive analytics solutions offered by Folio3 produce effective and fast results, enabling you to identify opportunities and anomalies in your business processes and strategy. -
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Neuton AutoML
Neuton.AI
Neuton, a no-code AutoML solution, makes Machine Learning available to everyone. Explore data insights and make predictions leveraging Automated Artificial Intelligence. • NO coding • NO need for technical skills • NO need for data science knowledge Neuton provides comprehensive Explainability Office©, a unique set of tools that allow users to evaluate model quality at every stage, identify the logic behind the model analysis, understand why certain predictions have been made. • Exploratory Data Analysis • Feature Importance Matrix with class granularity • Model Interpreter • Feature Influence Matrix • Model-to-Data Relevance Indicators historical and for every prediction • Model Quality Index • Confidence Interval • Extensive list of supported metrics with Radar Diagram Neuton enables users to implement ML in days instead of months.Starting Price: $0 -
28
OpenCV
OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.Starting Price: Free -
29
Protection!
jProductivity
Protection! - is a powerful multi-platform Licensing Toolkit and License Manager that provides the ability to add licensing into custom applications or components only allowing the permitted use according to the supplied license. Protection! uses high encryption technology and provides easy integration for software developers even for cross-platform products while being non-invasive for end users. Protection! License Manager offers a versatile solution for any licensing model. Protection! allows software vendors, publishers and developers to add licensing to Web, Enterprise, Server and Desktop applications. Provide users with the trial versions of their products. Significantly minimize or completely reduce unauthorized use of their applications and therefore dramatically increase company revenue. Increase revenue streams by implementing various licensing models while maintaining single code base and therefore offering higher flexibility to their customers. -
30
Obviously AI
Obviously AI
The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.Starting Price: $75 per month -
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Opsani
Opsani
We are the only solution on the market that autonomously tunes applications at scale, either for a single application or across the entire service delivery platform. Opsani rightsizes your application autonomously so your cloud application works harder and leaner so you don’t have to. Opsani COaaS maximizes cloud workload performance and efficiency using the latest in AI and Machine Learning to continuously reconfigure and tune with every code release, load profile change, and infrastructure upgrade. We accomplish this while integrating easily with either a single app or across your service delivery platform while also scaling autonomously across 1000’s of services. Opsani allows for you to solve for all three autonomously without compromise. Reduce costs up to 71% by leveraging Opsani's AI algorithms. Opsani optimization continuously evaluates trillions of configuration permutations and pinpoints the best combinations of resources and parameter settings.Starting Price: $500 per month -
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Lumada IIoT
Hitachi
Embed sensors for IoT use cases and enrich sensor data with control system and environment data. Integrate this in real time with enterprise data and deploy predictive algorithms to discover new insights and harvest your data for meaningful use. Use analytics to predict maintenance problems, understand asset utilization, reduce defects and optimize processes. Harness the power of connected devices to deliver remote monitoring and diagnostics services. Employ IoT Analytics to predict safety hazards and comply with regulations to reduce worksite accidents. Lumada Data Integration: Rapidly build and deploy data pipelines at scale. Integrate data from lakes, warehouses and devices, and orchestrate data flows across all environments. By building ecosystems with customers and business partners in various business areas, we can accelerate digital innovation to create new value for a new society. -
33
scikit-learn
scikit-learn
Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.Starting Price: Free -
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Alibaba Cloud Machine Learning Platform for AI
Alibaba Cloud
An end-to-end platform that provides various machine learning algorithms to meet your data mining and analysis requirements. Machine Learning Platform for AI provides end-to-end machine learning services, including data processing, feature engineering, model training, model prediction, and model evaluation. Machine learning platform for AI combines all of these services to make AI more accessible than ever. Machine Learning Platform for AI provides a visualized web interface allowing you to create experiments by dragging and dropping different components to the canvas. Machine learning modeling is a simple, step-by-step procedure, improving efficiencies and reducing costs when creating an experiment. Machine Learning Platform for AI provides more than one hundred algorithm components, covering such scenarios as regression, classification, clustering, text analysis, finance, and time series.Starting Price: $1.872 per hour -
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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. -
36
Core ML
Apple
Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos or detect specific objects within a photo directly from its pixels. After you create the model, integrate it in your app and deploy it on the user’s device. Your app uses Core ML APIs and user data to make predictions and to train or fine-tune the model. You can build and train a model with the Create ML app bundled with Xcode. Models trained using Create ML are in the Core ML model format and are ready to use in your app. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Once a model is on a user’s device, you can use Core ML to retrain or fine-tune it on-device. -
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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. -
38
Google Cloud AutoML
Google
Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs. It relies on Google’s state-of-the-art transfer learning and neural architecture search technology. Cloud AutoML leverages more than 10 years of proprietary Google Research technology to help your machine learning models achieve faster performance and more accurate predictions. Use Cloud AutoML’s simple graphical user interface to train, evaluate, improve, and deploy models based on your data. You’re only a few minutes away from your own custom machine learning model. Google’s human labeling service can put a team of people to work annotating or cleaning your labels to make sure your models are being trained on high-quality data. -
39
Amazon SageMaker JumpStart
Amazon
Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can access built-in algorithms with pretrained models from model hubs, pretrained foundation models to help you perform tasks such as article summarization and image generation, and prebuilt solutions to solve common use cases. In addition, you can share ML artifacts, including ML models and notebooks, within your organization to accelerate ML model building and deployment. SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs, including TensorFlow Hub, PyTorch Hub, HuggingFace, and MxNet GluonCV. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis. -
40
Emly Labs
Emly Labs
Emly Labs is an AI framework designed to make AI accessible for users at all technical levels through a user-friendly platform. It offers AI project management with tools for guided workflows and automation for faster execution. The platform encourages team collaboration and innovation, provides no-code data preparation, and integrates external data for robust AI models. Emly AutoML automates data processing and model evaluation, reducing human input. It prioritizes transparency, with explainable AI features and robust auditing for compliance. Security measures include data isolation, role-based access, and secure integrations. Additionally, Emly's cost-effective infrastructure allows on-demand resource provisioning and policy management, enhancing experimentation and innovation while reducing costs and risks.Starting Price: $99/month -
41
Elham.ai
Elham.ai
Elham.ai is an automated machine-learning platform that lets users build and deploy AI models with zero coding required. It offers a no-code interface where you can upload your datasets, select problem types (e.g., classification, regression, etc.), and let Elham handle data preprocessing, feature engineering, model training, evaluation, and deployment. It integrates with ChatGPT/OpenAI via Zapier, which allows transforming, summarizing, or analyzing integration data using leading AI models. It also has sign-up/login workflows, suggesting teams can start using it directly. It aims to convert raw data into actionable insights and streamline the end-to-end ML pipeline while hiding the complexities of model tuning and infrastructure setup.Starting Price: $559.75 per month -
42
NAVIK AI Platform
Absolutdata Analytics
An Advanced Analytics Software Platform That Helps Sales, Marketing, Technology, and Operations Leaders Make Great Business Decisions Based on Powerful Data-Driven Insights. Addresses the breadth of AI needs across data infrastructure, data engineering and data analytics. UI, workflows and proprietary algorithms are tuned to the unique needs of each client. Components are modular enabling custom configurations. Supports, augments and automates decision making. Elimination of human biases drives better business outcomes. The AI adoption rate is unprecedented. To stay competitive, leading companies need a rapid implementation strategy that scales. To create scalable business impact, combine these four distinct capabilities. -
43
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. High computational power has been required to process neural networks due to the number of layers and the volumes of data to train the networks. Furthermore, businesses are struggling to show results from deep learning experiments implemented in silos.
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44
Salford Predictive Modeler (SPM)
Minitab
The Salford Predictive Modeler® (SPM) software suite is a highly accurate and ultra-fast platform for developing predictive, descriptive, and analytical models. The Salford Predictive Modeler® software suite includes the CART®, MARS®, TreeNet®, Random Forests® engines, as well as powerful new automation and modeling capabilities not found elsewhere. The SPM software suite’s data mining technologies span classification, regression, survival analysis, missing value analysis, data binning and clustering/segmentation. SPM algorithms are considered to be essential in sophisticated data science circles. The SPM software suite‘s automation accelerates the process of model building by conducting substantial portions of the model exploration and refinement process for the analyst. We package a complete set of results from alternative modeling strategies for easy review. -
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Seminole
GladeSoft
Seminole is an embeddable webserver toolkit designed to be non-invasive and easily retrofitted to existing applications, lightweight with low resource consumption, and highly reliable with proper standards compliance and security safeguards. Written using a subset of C++, Seminole provides a modular, high-level API which simultaneously insulates the client programmer from complicated protocol details while allowing total control over low-level operation when necessary. Add in the optional Application Framework for a complete stateful and message-based development environment. Another important feature Seminole has is a powerful discovery service. The Seminole discovery protocol uses IP multicast to find locate Seminole instances even if you don't know the address of the devices. Additionally the discovery protocol can send small amounts of status information periodically. -
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AutoKeras
AutoKeras
An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras supports several tasks with an extremely simple interface. -
47
Synerise
Synerise
Synerise is an AI-driven Customer Data & Experience Platform (CDXP). Comprehensive, data-driven solution that centralizes and utilizes customer data to enhance marketing and engagement. Leveraging advanced artificial intelligence, Synerise aggregates data from various sources, creating detailed, real-time customer profiles. Key Strengths of Synerise Synerise excels in several key areas that set it apart from other platforms: - Real-time capabilities. Powered by TerrariumDB, our proprietary database engine designed specifically for behavioural intelligence, real-time computing - AI Engine. The quality of AI algorithms confirmed by successful participation in: Rakuten Data Challenge 2020; Twitter RecSys AI Challenge 2021; KDD Cup 2021; Booking.com AI Challenge 2021 - Time-To-Market. Confirmed by numerous successful implementations across various clients from various industries. -
48
FauxPilot
FauxPilot
FauxPilot is an open source, self-hosted alternative to GitHub Copilot. It utilizes the SalesForce CodeGen models on NVIDIA's Triton Inference Server with the FasterTransformer backend for local code generation. It requires Docker, an NVIDIA GPU with sufficient VRAM, and the ability to split the model across multiple GPUs if needed. The setup involves downloading models from Hugging Face and converting them for FasterTransformer compatibility.Starting Price: Free -
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The IBM z/OS Authorized Code Scanner (zACS) is a priced feature of z/OS version 2 release 4 and above to help support clients in their efforts to strengthen the security posture of the z/OS. The scanner searches for potential vulnerabilities within the Authorized Program Facility (APF) code libraries. Basic & advanced levels of testing for PCs & SVCs. AC(1) parameter testing for batch and USS environments. Visual z/OSMF experience providing diagnostics for remediation. Feeds off z/OS recovery processing non-invasively. Designed to run on production systems. Can automatically capture dumps for problem analysis.
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JADBio AutoML
JADBio
JADBio is a state-of-the-art automated Machine Learning Platform without the need for coding. With its breakthrough algorithms it can solve open problems in machine learning. Anybody can use it and perform a sophisticated and correct machine learning analysis even if they do not know any math, statistics, or coding. It is purpose-built for life science data and particularly molecular data. This means that it can deal with the idiosyncrasies of molecular data such as very low sample size and very high number of measured quantities that could reach to millions. Life scientists need it to understand what are the features and biomarkers that are predictive and important, what is their role, and get intuition about the molecular mechanisms involved. Knowledge discovery is often more important than a predictive model. So, JADBio focuses on feature selection and its interpretation.Starting Price: Free