Machine learning is a computing technology that enables computers to explore, learn, and modify their analytical functionalities when exposed to new data sets, without being explicitly programmed. It is also used to capture data and consequently run discrete modelers to create patterns for subsequent processing, analysis, and interpretations required for real-time decision making.

The global machine learning market is expected to grow from USD 1.41 Billion in 2017 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1%. The main driving factors for the market are proliferation in data generation and technological advancement.

In the services segment, the managed service segment is expected to grow at a higher CAGR, whereas professional service segment is expected to be a larger contributor during the forecast period. The managed service is said to be growing faster, as it helps organizations to increase efficiency and save costs for managing on-demand machine learning services. The growth of the professional services segment is mainly governed by the complexity of operations and increasing deployment of machine learning solutions.

In the deployment mode segment, the cloud deployment mode is expected to hold the largest market share and grow at the highest CAGR during the forecast period. Flexibility, automated software updates, disaster recovery through cloud-based backup systems, increased collaboration, monitoring document version control, and data loss prevention with robust cloud storage facilities are some of the crucial benefits that have resulted in the adoption of cloud-based delivery models for machine learning software solutions and services.

In the organization size segment, the large enterprises segment is expected to have the largest market share, whereas the SMEs segment is expected to grow at the highest CAGR during the forecast period. The rapidly emerging and highly active SMEs have increased the adoption of machine learning solutions and services globally, as a result of the growing digitization and increased cyber risks to critical business information and data. Large enterprises have been heavily adopting machine learning to extract the required information from a large amount of data and forecast the outcome of various problems.

In the verticals segment, the Banking, Financial Services, and Insurance (BFSI) vertical is expected to be the highest contributor, whereas the healthcare and life sciences vertical is projected to grow at highest CAGR during the forecast period. Both the verticals generate data in a huge amount every second, and there is accelerated demand for data management technologies such as machine learning and predictive analytics in order to extract business critical insights from this ever-increasing data. The other industry verticals, such as manufacturing, telecommunication, energy and utilities, retail, and government and defense are contributing significantly to the machine learning market. These verticals are also expected to witness significant growth rates during the forecast period due to the increased concerns for managing the complex business processes with improved efficiency and lowering the overall costs.

The global machine learning market has been segmented on the basis of regions into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. North America is estimated to be the largest revenue-generating region. This is mainly because, in the developed economies of the US and Canada, there is a high focus on innovations obtained from R&D. These regions have the most competitive and rapidly changing machine learning market in the world. The APAC region is expected to be the fastest-growing region in the machine learning market. The increased awareness for business productivity, supplemented with competently designed machine learning solutions offered by vendors present in the APAC region, has led APAC to become a highly potential market.

The major issue faced by most of the organizations while incorporating machine learning in their business process is the lack of skilled employees including analytical talent, and the demand for those who can monitor analytical content is even greater.

The major vendors that offer machine learning solutions across the globe are Microsoft Corporation (Washington, US), IBM Corporation (New York, US), SAP SE (Walldorf, Germany), SAS Institute Inc. (North Carolina, US), Google, Inc. (California, US), Amazon Web Services Inc. (Washington, US), Baidu, Inc. (Beijing, China), BigML, Inc. (Oregon, US), Fair Isaac Corporation (FICO) (California, US), Hewlett Packard Enterprise Development LP (HPE) (California, US), Intel Corporation (California, US), KNIME.com AG (Zurich, Switzerland), RapidMiner, Inc. (Massachusetts, US), Angoss Software Corporation (Toronto, Canada), H2O.ai (California, US), Alpine Data (California, US), Domino Data Lab, Inc. (California, US), Dataiku (Paris, France), Luminoso Technologies, Inc. (Massachusetts, US), TrademarkVision (Pennsylvania, US), Fractal Analytics Inc. (New Jersey, US), TIBCO Software Inc. (California, US), Teradata (Ohio, US), Dell Inc. (Texas, US), and Oracle Corporation (California, US).

VISIONARY LEADERS

Vendors who fall into this category receive high scores for most of the evaluation criteria. They have a strong and established product portfolio and a very strong market presence. They provide mature and reputable machine learning solutions. They also have strong business strategies. Microsoft, IBM Corporation, SAP SE, SAS Institute Inc., Google Inc., and Amazon Web Services, Inc. are the vendors who fall into the visionary leaders’ category.

INNOVATORS

Innovators in the MicroQuadrant are vendors that have demonstrated substantial product innovations as compared to their competitors. They have a much-focused product portfolio. However, they do not have a very strong growth strategy for their overall business. Baidu, Inc., BigML, Inc., FICO, HPE, Intel Corporation, KNIME.com AG, RapidMiner, Inc., Dataiku and Angoss Software Corporation are the vendors who fall into the innovator's category.

DYNAMIC Differentiators

They are established vendors with very strong business strategies. However, they are low in their product portfolios. They focus on specific type of technology related to the product. Dell and Oracle Corporation are the vendors who fall into the dynamic differentiators’ category.

EMERGING COMPANIES

They are vendors with niche product offerings and are starting to gain their position in the market. They do not have much strong business strategies, as compared to other established vendors. They might be new entrants in the market and require some more time to get significant traction in the market. H2O.ai, Alpine Data, Domino Data Lab, Inc. Luminoso Technologies, Inc., Skytree Inc., Fractal Analytics Inc., TIBCO Software Inc., and Teradata are the vendors who fall into the emerging companies’ category.

TOP VENDORS
In Machine Learning Software

  1. IBM CORPORATION
    0 Reviews
    3.7
  2. SAS INSTITUTE INC
    0 Reviews
    3.5
  3. MICROSOFT CORPORATION
    0 Reviews
    3.3

Find the best Machine Learning Software solution for your business, using ratings and reviews from buyers, analysts, vendors and industry experts

Filter Software

Sectors

Regions

  • All
  • Asia-Pacific
  • Europe
  • Latin America
  • Middle East and Africa
  • North America

Machine Learning Software Quadrant

Comparing 38 vendors in Machine Learning Software across 114 criteria.
Request for a free evaluation.
ASK OUR ANALYST
Tell us about your key problems, key buying criteria

KEY BUYING CRITERIA

Below criteria are most commonly used for comparing Machine Learning Software tools.
Product Maturity
Company Maturity
Most IMPORTANT
0.0
0.0
0.0
Breadth and Depth of Product Offerings
3.65
3.20
3.45
Product Features and Functionality
4.35
4.30
3.65
Focus on Product Innovation
2.90
2.75
3.30
Product Differentiation and Impact on Customer Value
3.60
3.00
3.00
Product Quality and Reliability
3.85
3.70
3.45
LEAST IMPORTANT LESS IMPORTANT

TOP VENDORS

  • It also helps to anticipate customer and business needs more accurately. IBM Watson machine learning service helps enterprises to use their data to create, train, and deploy self-learning models. IBM data science experience is a cloudbased, social workspace that helps data professionals to consolidate, create, and collaborate across multiple open sources tools, such as R and Python.

    BUYERS
    VENDORS
    EXPERTS
    3.7
    ANALYSTS
     
    • Enterprise
    • New York, US
    • Founded: 1911
    • $50 BN to $100 BN
    • 1,00,001 to 5,00,000
  • Its major features are automated model tuning, powerful data manipulation and management, flexible web-based programming environment, integrated text analytics, model assessment and scoring, and modern statistical, data mining, and machine-learning techniques.

    BUYERS
    VENDORS
    EXPERTS
    3.5
    ANALYSTS
     
    • Enterprise
    • North Carolina, US
    • Founded: 1976
    • $1BN to $5BN
    • 10,001 to 15,000
  • Azure Machine Learning is a fully managed service for advanced analytics in the cloud. It enables enterprises to build advanced analytic web services quickly and eradicate much of the heavy lifting associated with deploying machine learning in modern data-driven applications.

    BUYERS
    VENDORS
    EXPERTS
    3.3
    ANALYSTS
     
    • Enterprise
    • Washington, US
    • Founded: 1975
    • More than $100 BN
    • 1,00,001 to 5,00,000
  • The engine can perform large scale training on a managed cluster and can also manage the trained models for large scale online and batch predictions. Major features of Cloud Machine Learning Engine include portable models, notebook developer experience, scalable service, managed service, HyperTune, and the ability to discover and share samples.

    BUYERS
    VENDORS
    EXPERTS
    3.2
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1998
    • More than $100 BN
    • 75,001 to 1,00,000
  • The foundation offers instantly consumable services, such as image processing, natural language processing, and tabular and time-series processing that help enterprises to learn from data, extract knowledge, and gain new insights. The foundation helps organizations to incorporate intelligence into enterprise applications, without massive computing or data scientists.

    BUYERS
    VENDORS
    EXPERTS
    3.1
    ANALYSTS
     
    • Enterprise
    • Walldorf, Germany
    • Founded: 1972
    • 501 to 1,000
  • Amazon Machine Learning eases the job of obtaining predictions for user’s application using simple APIs without the need to implement custom prediction generation code or handle any infrastructure. It is considered to be highly scalable, and has the ability to generate billions of predictions on a daily basis and can serve those predictions in real time and at a high throughput as well.

    BUYERS
    VENDORS
    EXPERTS
    3.0
    ANALYSTS
     
    • Enterprise
    • Washington, US
    • Founded: 1994
    • More than $100 BN
    • 501 to 1,000
  • The company has developed machine learning algorithms for voice and image recognition, as well as natural language processing, to help provide smarter, more useful, and more personalized search results. Baidu makes its technology available to other companies to develop their algorithms and applications. The company has made most of its software and systems open source and provided access to it on an “as-a-service” basis.

    BUYERS
    VENDORS
    EXPERTS
    2.7
    ANALYSTS
     
    • Startup
    • 501 to 1,000
  • The major business functions where the company uses AI and machine learning are financial crimes, marketing, cybersecurity, customer management, threat detection, and strategic planning. FICO has more than 130 patents in analytics and decision management technology, including 70 in AI.

    BUYERS
    VENDORS
    EXPERTS
    2.6
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1956
    • $500MN to $1BN
    • 1,001 to 5,000
  • BUYERS
    VENDORS
    EXPERTS
    2.6
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1977
    • 1,00,001 to 5,00,000
  • BUYERS
    VENDORS
    EXPERTS
    2.5
    ANALYSTS
     
    • Enterprise
    • Texas, US
    • Founded: 1984
    • $50 BN to $100 BN
    • 1,00,001 to 5,00,000
  • BigMLer is a free and an open-source tool, which aids users to perform refined machine learning workflows by typing a single line in the command prompt. BigML-GAS is an add-on for Google Sheet, which puts in the missing values in a particular spreadsheet by utilizing its existing models and clusters. BigMLX is an app for Mac operating system, which provides the ability to build models and predict the outcomes by using the drag and drop functions on a Mac desktop.

    BUYERS
    VENDORS
    EXPERTS
    2.5
    ANALYSTS
     
    • Startup
    • Corvallis, OR, US
    • Founded: 2011
    • 1 to 50
  • With Sparkling Water, users can drive computation from Scala/R/Python and utilize the H2O Flow UI. Recently, the company introduced Driverless AI, which helps to prepare data, calibrate parameters, and determine the optimal algorithms for tackling specific business problems with machine learning. Furthermore, it automates feature engineering, the process by which key variables are selected to build a model.

    BUYERS
    VENDORS
    EXPERTS
    2.3
    ANALYSTS
     
    • Enterprise
    • 501 to 1,000
  • It enables users to apply machine learning to applications and big data analysis, to analyze and extract insights from the text, audio, video, and image files, and build cognitive apps with machine learning APIs. Major features of the platform are diverse support, extensive composable APIs, cloud-based consumption, and rich developer ecosystem.

    BUYERS
    VENDORS
    EXPERTS
    2.3
    ANALYSTS
     
    • Enterprise
    • Palo Alto, California, United States
    • Founded: 2015
    • 10,001 to 15,000
  • Built on a hardware foundation that includes computing, memory, storage, and network, these platforms include an optimized, scalable software stack for predictive analytics.

    BUYERS
    VENDORS
    EXPERTS
    2.3
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1968
    • $50 BN to $100 BN
    • 1,00,001 to 5,00,000
  • BUYERS
    VENDORS
    EXPERTS
    2.2
    ANALYSTS
     
    • Startup
    • Zurich, Switzerland
    • Founded: 2008
    • Below $10 MN
    • 1 to 50
  • BUYERS
    VENDORS
    EXPERTS
    2.2
    ANALYSTS
     
    • Startup
    • New York, US
    • Founded: 2013
    • $11MN to $50MN
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    2.2
    ANALYSTS
     
    • Startup
    • Massachusetts, US
    • Founded: 2006
    • Below $10 MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    2.1
    ANALYSTS
     
    • Startup
    • Ontario, Canada
    • Founded: 1984
    • Below $10 MN
    • 1 to 50
  • BUYERS
    VENDORS
    EXPERTS
    2.1
    ANALYSTS
     
    • Enterprise
    • San Francisco, California, US
    • Founded: 2010
    • $5BN to $10BN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    2.0
    ANALYSTS
     
    • Enterprise
    • San Mateo, California, United States
    • Founded: 2000
    • 1,001 to 5,000
  • BUYERS
    VENDORS
    EXPERTS
    2.0
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1997
    • $500MN to $1BN
    • 1,001 to 5,000
  • BUYERS
    VENDORS
    EXPERTS
    1.9
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2013
    • Below $10 MN
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    1.9
    ANALYSTS
     
    • Enterprise
    • California, US
    • Founded: 1979
    • $1BN to $5BN
    • 10,001 to 15,000
  • BUYERS
    VENDORS
    EXPERTS
    1.6
    ANALYSTS
     
    • Enterprise
    • 501 to 1,000
  • BUYERS
    VENDORS
    EXPERTS
    1.5
    ANALYSTS
     
    • Startup
    • CAMBRIDGE, Massachusetts, US
    • Founded: 2010
    • Below $10 MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2013
    • Below $10 MN
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2005
    • $11MN to $50MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • SME
    • California, US
    • Founded: 1997
    • $101MN to $500MN
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • Illinois, US
    • Founded: 2013
    • Below $10 MN
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • Connecticut, US
    • Founded: 2006
    • Below $10 MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2007
    • Below $10 MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2008
    • 101 to 500
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • SME
    • New York, US
    • Founded: 1975
    • $101MN to $500MN
    • 1,001 to 5,000
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • Bracknell Forest, UK
    • Founded: 1987
    • Below $10 MN
    • 51 to 100
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Enterprise
    • Pennsylvania, US
    • Founded: 1993
    • $1BN to $5BN
    • 1,001 to 5,000
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • California, US
    • Founded: 2012
    • $11MN to $50MN
    • 501 to 1,000
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Startup
    • New York, US
    • Founded: 2004
    • Below $10 MN
    • 501 to 1,000
  • BUYERS
    VENDORS
    EXPERTS
    ANALYSTS
     
    • Enterprise
    • Washington, US
    • Founded: 2003
    • $500MN to $1BN
    • 1,001 to 5,000

POTENTIAL BUYERS AND THEIR PROBLEMS

 

Questions & Answers

TOP REVIEWS

Looking for Machine Learning Software? Get help

BE THE FIRST ONE TO REVIEW

Share your experience with potential buyers.