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Global Machine Learning Market (2018 – 2023)
Updated On: 09 January, 2019 | No of Pages: 90-100 | Format: PDF | SKU: 201859
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Evolution of technology has brought about the advent of computers which are competent to learn and enhance their performance on the basis of past experiences. This science is known as machine learning. It is an application of artificial intelligence (AI) where separate algorithms and human intervention are not needed to be preprogrammed into the computer in order to take on unfamiliar scenarios. In recent times, this market has gained significant importance due to the increased generation of data and the need to process it to obtain meaningful insights. The value of the machine learning market is expected to reach USD 19.40 Bn by 2023, expanding at a compound annual growth rate (CAGR) of 48.3% during the 2018-2023 period.

Global Machine Learning Market (2018-2023)

Applications segment insights:

Global trends indicate the increased application of machine learning techniques in the healthcare, financial, and retail sectors. The world is moving towards a connected business ecosystem that makes data-powered decisions. In 2018, retail surpassed the banking, financial services and insurance (BFSI) sub-segment to become the industry leader in terms of machine learning expenditure. Retail firms will be investing in a plethora of use cases, including expert shopping advisors and product recommendations, and automated customer service agents. The spending by the BFSI sub-segment will be targeted towards fraud analysis and investigation, automated threat intelligence and prevention systems, along with program advisors and recommendation systems.

Deployment mode segment insights:

In terms of deployment mode, the cloud segment will capture a higher market share during the forecast period, owing to increased adoption by various industries across the world. Because of the high costs involved with on-premises deployment, industry professionals will be putting more emphasis on working on the cloud deployment mode, owing to its low-cost structure.

Regional segment insights:

North America will lead with regard to innovation in machine learning, and will occupy a major share of the global market. The growth of mobile computing systems in the last decade, which paved the way for easy collection and transmission of data across platforms, has led to the emergence of ‘Big Data’, which machine learning is hugely dependent on now. This has given a considerable boost to the market in North America. The Asia-Pacific region will witness the highest growth rate during the forecasted period. In Latin America, the unskilled workforce has found it challenging to pick up the expertise needed for machine learning processes. This will act as a hindrance to the further development of the market. The adoption of machine learning in all the sectors will be a slow process in Africa, unless infrastructure and consumer spending power improves.

Companies covered:

  • Microsoft
  • Google Inc.
  • IBM Watson
  • Amazon
  • Baidu
  • Intel
  • Apple Inc.
  • Darktrace
  • Ayasdi
  • Luminoso

 

Customizations available

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Estimated Delivery Time: 10 business days

Chapter 1. Executive summary

 

1.1. Market scope and segmentation

1.2. Key questions answered

1.3. Executive summary

 

Chapter 2. Global machine learning market – overview

 

2.1. Global market overview - historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), geography-wise market revenue (USD Bn), and market attractiveness analysis

2.2. Global market drivers

2.3. Global market trends

2.4. Global market challenges

2.5. Value chain analysis  

2.6. Market segmentation based on application - key market observations

2.7. Market segmentation based on deployment mode (cloud deployment and on-premise deployment) – market size (USD Bn), and key market observations

 

Chapter 3. North America machine learning market

 

3.1. Regional market overview - historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), and key market observations

3.2. Market drivers

3.3. Market challenges

3.4. Market trends

3.5. Market segmentation based on application - key market observations

3.6. Market segmentation based on deployment mode (cloud deployment and on-premise deployment) – market size (USD Bn), and key market observations

  

Chapter 4. Europe machine learning market

 

4.1. Regional market overview - historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), and key market observations

4.2. Market drivers

4.3. Market challenges

4.4. Market trends

4.5. Market segmentation based on application - key market observations

4.6. Market segmentation based on deployment mode (cloud deployment and on-premise deployment) – market size (USD Bn), and key market observations

 

Chapter 5. Asia-Pacific machine learning market

 

5.1. Regional market overview - historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), and key market observations

5.2. Market drivers

5.3. Market challenges

5.4. Market trends

5.5. Market segmentation based on application - key market observations

5.6. Market segmentation based on deployment mode (cloud deployment and on-premise deployment) – market size (USD Bn), and key market observations

Chapter 6. Competitive landscape

6.1. Microsoft

6.1.a. Company snapshot

6.1.b. Product offerings

6.1.c. Growth strategies

6.1.d. Initiatives

6.1.e. Geographical presence

6.1.f. Key numbers

6.2. Google Inc.

6.2.a. Company snapshot

6.2.b. Product offerings

6.2.c. Growth strategies

6.2.d. Initiatives

6.2.e. Geographical presence

6.2.f. Key numbers

 

6.3. IBM Watson

6.3.a. Company snapshot

6.3.b. Product offerings

6.3.c. Growth strategies

6.3.d. Initiatives

6.3.e. Geographical presence

6.3.f. Key numbers

 

6.4. Amazon

6.4.a. Company snapshot

6.4.b. Product offerings

6.4.c. Growth strategies

6.4.d. Initiatives

6.4.e. Geographical presence

6.4.f. Key numbers

 

6.5. Baidu

6.5.a. Company snapshot

6.5.b. Product offerings

6.5.c. Growth strategies

6.5.d. Initiatives

6.5.e. Geographical presence

6.5.f. Key numbers

 

6.6. Intel

6.6.a. Company snapshot

6.6.b. Product offerings

6.6.c. Growth strategies

6.6.d. Initiatives

6.6.e. Geographical presence

6.6.f. Key numbers

 

6.7. Apple Inc.

6.7.a. Company snapshot

6.7.b. Product offerings

6.7.c. Growth strategies

6.7.d. Initiatives

6.7.e. Geographical presence

6.7.f. Key numbers

 

6.8. Darktrace

6.8.a. Company snapshot

6.8.b. Product offerings

6.8.c. Growth strategies

6.8.d. Initiatives

6.8.e. Geographical presence

6.8.f. Key numbers

 

6.9. Ayasdi

6.9.a. Company snapshot

6.9.b. Product offerings

6.9.c. Growth strategies

6.9.d. Initiatives

6.9.e. Geographical presence

6.9.f. Key numbers

 

6.10. Luminoso

6.10.a. Company snapshot

6.10.b. Product offerings

6.10.c. Growth strategies

6.10.d. Initiatives

6.10.e. Geographical presence

6.10.f. Key numbers

6.a. Major developments

6.b. Startups and disruptors

 

Appendix

  • Research methodology
  • Assumptions
  • About Netscribes Inc.   

Companies profiled

  • Microsoft
  • Google Inc.
  • IBM Watson
  • Amazon
  • Baidu
  • Intel
  • Apple Inc.
  • Darktrace
  • Ayasdi
  • Luminoso

 

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