Rising Technological Advancements Followed by Proliferation in Data Generation to Drive Machine Learning Market: Ken Research


Machine Learning is a fragment of Artificial Intelligence (AI) that allows computers to learn without existence detailed programmed. It’s primarily emphasis on the development of the computers programs that can be switch when visible to new data. It provides multiple uses concerning with safety & security for instance face recognition, face detection, image classification, antivirus, anti spam, speech recognition, signal diagnosing and genetic. It is can also be defined by many algorithms such as supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning. The algorithms use various methods and techniques such as sparse dictionary learning, feature learning, anomaly detection and association rules to improve their performance.

According to study, “Global Machine Learning Market (2018-2023)” some of the major companies that are currently working in the global machine learning market are Microsoft Corp., IBM Watson, Facebook, Fair Isaac Corp., SAS Institute Inc., Amazon Web Services Inc., Hewlett Packard Enterprise Development LP, Pindrop Inc., H2O.ai Inc., Apple Inc., Bigml Inc., Cisco Inc., TwitterInc, SAP SE, Baidu Inc., Qubit Inc., Luminoso, Nuance Communications, Wipro Inc., Google Inc., Uber, Intel Corp.

On the basis of components, the global machine learning market is segmented into cloud,software tools, and web-based application programming interfaces (APIs). Based on the services market is segmented into professional services & managed services. Based on organization size, the market is segmented into small & medium enterprises (SMEs) and large enterprises. Additionally, on the basis of software, the market is segmented into NeuroSolutions, LIONsolver, Oracle Data Mining, SequenceL, SAP Leonardo Machine Learning, CNTK, Mallet, Deep learning etc.

On the basis of application market is segmented into banking, financial services and insurance (BFSI), healthcare& life sciences, retail, telecommunication, automotive, energy & utilities and government& defense. BFSI is further classified into digital assistance, sales & marketing campaign management, customer segmentation, sales & marketing campaign management, investment prediction and fraud & risk management etc. Healthcare & life sciences is sub-segmented into image analytics, drug discovery or manufacturing, disease identification & diagnosis and personalized treatment. Retail includes upsells & cross channel marketing, inventory planning, segmentation & targeting and recommendation engines etc. Telecommunication segment is sub-segmented into network security, customer analytics and network optimization etc. Energy & utilities includes carbon emission, power or energy usage analytics, smart grid management and seismic data processing.

Some of the key benefits are continuous improvements, data mining, and automation of tasks, competencies to handle multi-dimensional & multi-variety data and efficient utilization of resources. However market is also impacted by some of the drawbacks such as acquisition of relevant data and interpretation of results.

The market of machine learning is generally driven by rising technological advancements followed by proliferation in data generation, efficient operations & improves sales revenue, rising demand for superior custom services and availability of massive amount of data. Apart from advantages, some of the key challenges are data security, lack of cloud infrastructure, rising concerns regarding data security & governance, lack of skilled employees and ethical implication of algorithms deployed etc. In addition, some of the rising new opportunities are increase in the adoption of modern applications and increasing demand for intelligent business processes.

It is expected that the global machine learning market to reach at US$ 23.4 billion, by 2023. In upcoming years, it is predicted that the market to grow fast pace owing to increasing adoption of robotic process automation.

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Ankur Gupta, Head Marketing & Communications




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