Skip to main content

Machine Learning Market Product Portfolio, Financial Performance, Key Strategies, Recent Developments, Future Plans

Machine learning is a branch of artificial intelligence that enables machines to learn directly from data, experience, and examples. By permitting computers to execute specific tasks smartly, machine learning allows computers to carry complex processes by learning from examples or data, rather than following pre-programmed rules. Increasing volume of data being generated across industry verticals creates an exhaustive repository for machines to learn from, something that is further backed by rapid strides made in processing power of computers, in turn enhancing the analytical capabilities of machine learning systems. 
  

Increasing advancements in technology leading to higher accuracy of systems fueling market growth  
People interact with various systems, which are based on machine learning such as recommender systems, voice recognition systems, and image recognition systems. Rapid advancement in technology in image recognition system has increased the accuracy of the system, which has fueled the demand for machine learning in various systems. For instance, in image labeling challenge, the accuracy of machine learning was 72% in 2010 and it reached to 96% in 2015. The ability of machines to process large volumes of data and to use the data for prediction have made the machine learning a key tool in various applications such as BFSI, healthcare etc.  

Integration of machine learning in robotics has fueled growth of the machine learning market
Rampant advancements in robotic industry has created various innovations in robots with the integration of sensor technologies and materials. The advancements in machine learning have increased the capabilities of robots to contribute in applications such as drones and autonomous vehicles. Moreover, the increasing demand for advance robotic system in various verticals such as automotive, electronics, food and beverages, healthcare etc has fueled the market growth. According to International Federation of Robots, in 2016, around 294,000 units of industrial robots were deployed across the globe. For example: In 2016, Fanuc, a Japan-based company, announced development of a robot with deep reinforcement learning technique, which enables the robot to train itself over a very short time duration.


Machine learning Market Taxonomy
On the basis of application:
  • Banking, Financial Services, and Insurance
  • Education
  • Energy
  • Healthcare & Pharmaceuticals
  • Manufacturing
  • Public Services
  • Retail
  • Transport & Logistics
Machine learning market is expected to witness rampant growth due to growing healthcare sector in the near future.

Accuracy is one of the major concerns in the healthcare sector. Machine learning have the capabilities to provide more accurate diagnosis and healthcare services, which in turn has augmented demand for machine learning in healthcare sector. For instance, diagnosis of diabetic eye disease requires frequent examination of pictures at the back of an eye by the specialist. The features in the image helps to identify sensitivity of disease, which in turn, indicates fluid leakage and bleeding. Moreover, in 2016, Google has developed a deep learning algorithm, which analyze images and provides training to the system by using a data set of 128,000 images. Thus, the system diagnose the disease with a level of accuracy similar to human ophthalmologists. On similar lines, Google researchers are developing a deep learning algorithm for early diagnosis of skin cancer and breast cancer. 

Key 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 in the global machine learning market.

Comments

Popular posts from this blog

Top Technologies Shaping Future of Cybersecurity!!

The threat of Cyber attacks are growing day by day across the world hence led big concern on  Cybersecurity. Cyber security includes- Application security, Information security, Network security, Disaster recovery/business continuity planning, Operational security and End-user education Types of cybersecurity threats: Ransomware  Malware  Social engineering Phishing  Artificial Intilligence and Blockchain are the Technologies that will help the cybersecurity to boost. AI-based attacks that will operate completely independently, adapt, make decisions on their own and more.  Blockchains are moving from the realm of just fueling cryptocurrencies like Bitcoin to providing smart contracts, identity management, and multiple ways of proving integrity of data. They may also hold the key to defending against IoT attacks.

Transit Cards Market to Witness Enhanced Growth During 2018-2026

A transit card is a train, bus or metros pass or ticket that provides users the access to transportation services, either as part of a specific number of pre-purchased trips or boundless trips within a limited timeframe. Growing population and urbanization in emerging economies worldwide is increasing the demand for mobility. According to Population Reference Bureau Organization, in 2016, 7,418 million people accounted for the global population up from 7,336 million in 2015. For sample copy, download PDF @ https://www.coherentmarketinsights.com/insight/request-pdf/663 This increasing population has in turn increased demand for public transportation services in various countries worldwide. Public transportation has turned into the most favored method of transportation for individuals to avoid traffic congestion and air pollution. Travelling by trains, bus, and metros is generally more convenient, comfortable, and cost-effective. Public transport frameworks utilize modern ticketing...

Nanotech Sensor! Latest Update You Need To Know

Nanotech Sensor Scientists have developed a nanotech sensor that can turns molecular fingerprints into bar codes, according to a study published on June 7, 2018.  This study was conducted by the scientists at the EPFL’s School of Engineering and at Australian National University (ANU). Until now, infrared spectroscopy was the commonly used method to detect and analyze organic compounds. However, it required complicated procedures and large, expensive instruments, which made device miniaturization challenging. This led to the discovery of a compact and sensitive nanophotonic system that can identify a molecule’s absorption characteristics without using conventional spectrometry. Source :  https://www.coherentnews.com/scientists-develop-nanotech-sensor-that-turns-molecular-fingerprints-into-bar-codes/