Deep Learning Market: Business Opportunities, Current Trends,



Deep Learning Market

Deep learning, considered a subdomain of Machine Learning, is about algorithms and is largely inspired by the structure of the brain and a function called an artificial neural network. Technology is advancing at an alarming rate and the latest advances in artificial intelligence (AI) are simply overwhelming.

Deep learning needs high-end machines, unlike traditional machine learning algorithms. Moreover, in traditional machine learning techniques, the majority of the applied functionality must be identified by an expert in the field in order to reduce the complexity of the data and make the models more visible for the learning algorithms to work. However, deep learning learns high-level functionality from data incrementally, eliminating the need for domain expertise as well as feature extraction. Deep learning is also known as deep neural learning or deep neural network.

The penetration into Big Data Analytics is widely adopted by various business organizations as they collect a large amount of data according to the requirements of the organization. This generation of data is expected to increase further with upcoming technologies such as 5G. Therefore, it is believed that deep learning will find applications in the analysis of big data in order to extract sophisticated models from a large amount of data.

Artificial intelligence and deep learning can analyze huge volumes of customer data in seconds. It also provides information on the history of previous purchases and analyzes customer choices. Through these techniques, players can also understand the price preferences of customers. The increasing use of artificial intelligence in customer data analysis is expected to create plenty of opportunities for the global deep learning market.

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The Top Leading Players Covered In This Report: NVIDIA, Samsung Electronics, Intel Corporation, Xilinx, Qualcomm, Micron Technology, IBM, Google Inc., Microsoft Corporation, and Amazon Web Services. The market also has start-ups such as Mythic, Graphcore, Adapteva and Koniku operating worldwide., & More …

By hardware, CPU, GPU, FPGA, ASIC By solution, hardware, software, services
By End User, Automotive, Aerospace & Defense, Healthcare, Manufacturing, Marketing, Others

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Growing domestic demand and expanding pharmaceutical sector to drive deep learning demand in APAC region:
The Asia-Pacific region is expected to hold the largest market share in the global Deep Learning market during the forecast period 2019-2026. The growth in this region can be attributed to the presence of emerging economies like India, China, Japan, Vietnam and Indonesia, which account for the largest share in this region. India is one of the largest producers of Deep Learning and a major exporter of the product to various countries across the world. India accounts for around 80% of global deep learning exports. Favorable climatic conditions and the growth of agricultural inputs and related services like cold storage and warehousing in India are leading to increased production.

R&D activities:
Major players rely on strategic mergers and acquisitions to improve their market penetration. For example, after acquiring Nervana Systems in 2016, Intel introduced the Intel Nervana Neural Network Processor, the first silicon for a neural network processor. The technology helps end users create new sets of AI applications that maximize the amount of data processed. It also provides insight and helps businesses transform their business through deep learning technology.

Key questions addressed in the report:
What is the current scenario of the Global Deep Learning Market? How is the market going to prosper throughout the forecast period?

What emerging technologies and associated tools will benefit the market?

What is the current size of the global Deep Learning market?

Which segments are the most dynamic and important in the market? What is their market potential?

What are the determining factors that contribute to the market growth in the short, medium and long term?

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