Machine learning is a branch of artificial intelligence that enables machines to learn directly from data, experience, and examples. By allowing computers to perform specific tasks smartly, machine learning allows computers to perform complex procedures by learning from examples or data, rather than following pre-programmed rules. The increasing amount of data being generated across industry verticals creates an exhaustive repository for Machine learning, something that is supported by rapid advances made in the processing power of computers, in turn increasing the analytical capabilities of machine learning systems.
Growing advances in technology lead to higher accuracy of systems fueling the growth of the market
People interact with various systems that are based on machine learning such as recommendation systems, voice recognition systems and image recognition systems. Rapid advances in technology in image recognition systems have increased the accuracy of the system, which has fueled the demand for machine learning in various systems. For example, in the image labeling challenge, machine learning accuracy was 72% in 2010 and reached 96% in 2015. The ability of machines to process large amounts of data and use the data for prediction has made machine learning one. Critical equipment in various applications like BFSI, healthcare etc.
The integration of machine learning in robotics has fueled the growth of the machine learning market
Massive advances in the robot industry have led to various innovations in robots with the integration of sensor technologies and materials. Advances in machine learning have increased the capabilities of robots to contribute to applications such as drones and autonomous vehicles. Moreover, the increasing demand for advanced robotic system in various verticals such as automotive, electronics, food & beverage, healthcare etc. has fueled the growth of the market. According to the International Federation of Robots, in 2016, approximately 294,000 industrial robots were deployed around the world. For example: In 2016, a Japan-based company, Fanuc, announced the development of a robot with deep reinforcement learning technology, which enables the robot to train itself in a very short time span.
Machine Learning Market Taxonomy
On the basis of deployment model, the global machine learning market has been segmented into:
on-premises
cloud-based
On the basis of application, the global machine learning market has been segmented into:
Banking, Financial Services and Insurance
Education
energy
Healthcare & Pharmaceuticals
Production
public services
retail
Transport & Logistics
The machine learning market is expected to witness huge growth in the near future owing to the growing healthcare sector.
Accuracy is one of the major concerns in the healthcare sector. Machine learning has the potential to provide more accurate diagnostics and healthcare services, leading to an increase in the demand for machine learning in the healthcare sector. For example, the diagnosis of diabetic eye disease requires frequent examination of images of the back of the eye by a specialist. Image features help to identify disease susceptibility, which in turn indicates fluid leakage and bleeding. Also, in 2016, Google developed a deep learning algorithm, which analyzes images and provides training to the system using a data set of 128,000 images. Thus, the system diagnoses the disease with a level of accuracy similar to that of human ophthalmologists. Similarly, Google researchers are developing a deep learning algorithm for early diagnosis of skin cancer and breast cancer.
Major Companies in the Global Machine Learning Market
Microsoft Corporation, SAP SE, Sas Institute Inc., Amazon Web Services, Inc., Bigml, Inc., Google Inc., Fair Isaac Corporation, Hewlett Packard Enterprise Development Lp, and Intel Corporation are some of the major companies operating globally. have been Machine Learning Market.
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