On the basis of organization size, the market is segmented into Small and Medium Enterprises &
Large enterprises.
On the basis on Applications, the market is segmented into BFSI, Healthcare, Government,
Automotive, Education, Media &Entertainment, Defence, Telecom, and Retail & E-commerce
On the basis of Region, the market is segmented into North America, Europe, Asia-Pacific (APAC),
and Rest of the World
Regional Analysis:
The regional analysis of machine learning market is being studied for region such as Asia pacific,
North America, Europe and Rest of the World.
European region is expected to dominate in the Machine Learning market by the forecast period
owing to fast emerging of start-ups which mainly focus on innovation and commercialization of
machine intelligence technologies. London is Europe’s start up canter, mixing capital, proximity to
markets, and world-class research hubs. The Asia-Pacific region, though, is expected to emerge as a
lucrative market.
North America closely followed by Europe in Rapidly advancements in computer programs
category.
Industry News
June 4, 2018 DataRobot Puts the Power of Machine Learning In the Hands of Business
Analysts: DataRobot, the Boston based data science company give machine learning technology to
the business analyst who don’t have knowledge of machine learning or programming. Business
analyst uses automated ML to build and deploy accurate predictive models in a short span of time.
June 3, 2018 Amazon Alexa learns new trick: finding the right skill on its own: In a practical
use of artificial intelligence, the feature combines a customer request with a machine-learning
model to choose the right skill to use, without the consumer needing to know the name of the
skill. When a customer taps their Amazon Echo smart speaker and speaks without using a skill by
name, Alexa selects the best skill to call, based on the machine-learning model.
May 7, 2018 Microsoft continues its quest to bring machine learning to every application:
The company's focus this year is on two main areas i.e. customization and edge deployment. All the
machine learning services operates on two distinct phases. The first phase is building a model: a set
of test data is used to train neural networks to construct the model. The second phase is using the
model in which new data is fed into the model and an output is produced according to what the
neural nets learned