Machine Learning Tools
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The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to…
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Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
Boston based Botkeeper is the world's first and original robotic bookkeeper. The Botkeeper solution uses a combination of skilled accountants, machine learning, and AI to provide the best bookkeeping at the lowest possible cost. Instead of replacing your existing accounting software,…
RapidCanvas provides an enterprise-grade no-code platform for data practitioners to go from raw data to ML applications rapidly. RapidCanvas taps into full-cycle autoML and a network of domain experts to deliver results. The vendor states customers using RapidCanvas have reduced…
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An open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides…
Iguazio, headquartered in Herzliya, provides a Data Science Platform to automate machine learning pipelines. It aims to accelerate the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more…
IBM's Watson Visual Recognition was a machine learning application designed to tag and classify image data, and deployable for a wide variety of purposes. The service was discontinued in early 2021, and is no longer available.
AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed…
Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global…
IBM Machine Learning for z/OS® brings AI to transactional applications on IBM zSystems. It can embed machine learning and deep learning models to deliver real-time insight, or inference every transaction with minimal impact to operational SLAs.
Amazon offers Rekognition, an image and video visual analytics tool that is trained on locating and identifying labeled or tag-related objects, events, people, and also inappropriate content in images and video so that images and video can more safely and reliably be integrated and…
Bell Integrator offers Neuton, an automated machine learning (Automated ML) application supplying AI learning and assistance to analytics and or business processes.
MLReef is a Machine Learning development platform that aims to democratize ML innovation across the entire organization. Distributed ML Development: - up to 5X in ML development throughput - up to 85% less dependency on internal data science capacity - Distributed workload on complex…
The expert.ai NL Suite (formerly Cogito Intelligence Platform (CIP) from Expert System, rebranded expert.ai) performs analysis of unstructured data sets to organize, discover and explore information in order to support intelligence workflows by providing actionable insight as data…
Kortical is an end to end AI as a Service (AIaaS) platform designed to accelerate the creation, iteration, explanation and deployment of world-class machine learning models. The vendor describes the key benefits of Kortical is AutoML that writes custom machine learning solutions…
Kimola Cognitive is a Machine Learning Platform that enables users to grab reviews from 20+ channels and analyze + classify customer feedback -or any text data- automatically. Top features of Kimola Cognitive are: Scrape Web and Collect Reviews Data analysis starts with data collection,…
Gavagai Explorer is a text analysis tool for companies that want to keep track of what their customers think – regardless of which language they speak. Explorer analyzes texts in 47 languages. The texts get automatically analyzed and the results are presented in interactive and share-…
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research and by community contributors.
Amazon TensorFlow enables developers to quickly and easily get started with deep learning in the cloud.
Course5 Discovery is an AI-powered Augmented Analytics solution that aims to deliver fast, relevant, actionable and humanized insights across multiple consumption mediums and personas to create an insights-first culture that rewards data-driven decision making. Course5 Discovery…
Explorium, headquartered in San Mateo, provides an External Data Platform that automatically discovers thousands of relevant data signals and uses them to improve analytics and machine learning. The automated Explorium Platform enables organizations to discover and use third party…
The Appen platform combines human intelligence from over one million people all over the world with models to create training data for ML projects. Appen users can upload data to the Appen platform, and they provide the annotations, judgments, and labels needed to help create ground…
Users can build custom conversational experiences using Google Assistant’s voice and visual APIs. Take users on journeys through a product, using Assistant’s natural language understanding (NLU) capabilities and developer tools.
Streamlit is an open-source Python library designed to make it easy to build custom web-apps for machine learning and data science, from the company of the same name in San Francisco. Streamlit also hosts its community's Streamlit Component offered via API to help users get started.…
Azure OpenAI Service, a service from Microsoft's Azure suite available in preview, includes pre-generated AI models that enable users to apply advanced coding and language models to a variety of use cases, enabling new reasoning and comprehension capabilities for building applications.…
Learn More About Machine Learning Tools
What are Machine Learning Tools?
Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It’s called machine learning because the model “learns” as it is fed more and more data.
They can be used, for example, to build recommendation engines, predict search patterns, filter spam, build news feeds, detect fraud and security threats, and much more. There are four types of machine learning algorithms: supervised, unsupervised, semi-supervised, and reinforced.
Supervised algorithms are machine learning tools with training wheels. They require a person to program both the input and the desired output, as well as provide feedback as to the accuracy of the end results.
Unsupervised algorithms require very little human intervention by instead using an approach called “deep learning” to review massive banks of data and arrive at conclusions based on previous examples of training data; they are, therefore, generally used for more complex processing tasks such as image recognition, speech-to-text, and natural language generation.
Semi-supervised algorithms tend to fall in the middle ground.
Reinforced algorithms force models to repeat a process until it produces the most favorable outcomes. Attempts that produce these favorable outcomes are rewarded and attempts that produce unfavorable results are penalized until the algorithm learns the optimal process.
Machine Learning Tools' Features & Capabilities
Most vendors offering machine learning tools include:
- Data collection and preparation
- Model building
- Training and application deployment
Additional Tools
Some vendors also offer additional tools to
- Store aggregated data on the Cloud
- Build models with easy drag and drop capabilities
- Access libraries with pre-modeled routines and functions
Machine Learning Tools Comparison
When beginning your process for a machine learning tool with which to get started, walk through the following flow of questions to help you narrow down your options:
- Am I looking for a managed machine learning platform? (Think time-and-cost efficiency.)
- Do I need a mobile-supported tool?
- For what scripting language do I need support? (R, Python, Java, C++, etc.)
- If you're on a budget, ask yourself: Can I effectively manage my training data with the storage space I have? (You may need to consider moving to the cloud, which is typically more expensive.)
- Do I need support for multiple model types? (Binary, regression, multi-class, etc.)
- Would I prefer having an extensive library with which to start?
- Are my projects expected to grow (and thus requiring a need for scalability)?
- Do I need a full cycle deep learning system?
Ready to start comparing your shortlist head-to-head? Start a Machine Learning Tools comparison
Pricing Information
Many vendors offering machine learning tools will offer a free trial or a free version with a limited batch of predictions. There are several free and open-source machine learning platforms, like Google's Tensorflow, for developers on a budget. For paid plans, prices are generally Pay-As-You-Go, tiered by price per hour and training units, typically starting at $0.10/Unit/Hour. Deep learning capabilities are typically more expensive, at $1+/GPU/Hour.