Machine Learning Tools

Best Machine Learning Tools include:

Keras and Oracle Machine Learning.

Machine Learning Tools TrustMap

TrustMaps are two-dimensional charts that compare products based on trScore and research frequency by prospective buyers. Products must have 10 or more ratings to appear on this TrustMap.

Machine Learning Tools Overview

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.

Machine Learning Products

(1-25 of 125) Sorted by Most Reviews

RStudio

RStudio

Customer Verified
Top Rated

RStudio is a modular data science platform, combining open source and commercial products. The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to…

IBM Watson Studio on Cloud Pak for Data

IBM Watson Studio

Customer Verified
Top Rated

IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies…

Key Features

  • Connect to Multiple Data Sources (24)
    77%
    7.7
  • Flexible Model Publishing Options (24)
    75%
    7.5
  • Security, Governance, and Cost Controls (24)
    68%
    6.8
Jupyter Notebook

Jupyter Notebook

Customer Verified
Top Rated

Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and…

Key Features

  • Visualization (23)
    90%
    9.0
  • Interactive Data Analysis (23)
    88%
    8.8
  • Connect to Multiple Data Sources (24)
    83%
    8.3
Kira Systems

Kira

Customer Verified
Top Rated

Kira is software that excels at searching and analyzing contract text. Kira offers pre-built, machine learning models covering due diligence, general commercial, corporate organization, real estate and compliance. Using Kira Quick Study, anyone can train additional models that can…

TensorFlow

TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.

OpenText Magellan

OpenText Magellan Analytics Suite leverages a comprehensive set of data analytics software to identify patterns, relationships and trends through data visualizations and interactive dashboards.

Oracle Machine Learning (formerly Oracle Advanced Analytics)

Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.

Databricks Lakehouse Platform (Unified  Analytics Platform)

Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data…

Google Cloud AI

Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.

Keras

Keras is a Python deep learning library

Amazon SageMaker

Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Azure Machine Learning Studio

Microsoft's Azure Machine Learning Studio 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.

DataRobot

The DataRobot enterprise 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…

Cloudera Data Platform

Cloudera Data Platform (CDP), launched September 2019, is designed to combine the best of Hortonworks and Cloudera technologies to deliver an enterprise data cloud. CDP includes the Cloudera Data Warehouse and machine learning services as well as a Data Hub service for building custom…

botkeeper

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,…

Kortical

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…

Amazon Deep Learning AMIs

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…

IBM Watson Natural Language Understanding

IBM offers Watson Natural Language Understanding, an NLP application supplying interpretation of unstructured textual data and language concept models.

IBM Watson Visual Recognition

IBM offers Watson Visual Recognition, a machine learning application designed to tag and classify image data, and deployable for a wide variety of purposes.

Amazon Tensor Flow

Amazon TensorFlow enables developers to quickly and easily get started with deep learning in the cloud.

IBM Watson Machine Learning

IBM Watson Machine Learning allows businesses to deploy self-learning models at scale, allowing AI to deployed in applications and available free to try, free for limited use (5 deployed models and 5,000 predictions per month), or at cost for high workloads priced per thousands of…

Caffe Deep Learning Framework

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.

Intel Deep Learning Cloud

The Intel Deep Learning Cloud, or Intel Nervana, is a deep learning framework based on Nervana Systems' Nervana Cloud AI framework, with industry leading performance on GPUs thanks to its custom assembly kernels and optimized algorithms. Intel acquired Nervana Systems in 2016.

Frequently Asked Questions

What is machine learning?

Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", to make predictions or decisions without being explicitly programmed to do so.

What is the difference between deep learning and machine learning?

Firstly, deep learning is a type of machine learning. Standard machine learning requires training data to make predictions. However, deep learning programs as a subset of machine learning are capable of making a prediction based on their own data, referred to as its artificial neural network.

What are machine learning applications?

Machine learning applications help you easily build AI algorithms that learn as they go. They typically provide implementations or libraries of distributed or scalable machine learning algorithms for users. They can be particularly cost-productive and time-saving.