Chapter 1: Executive summary 1.1. Market scope and segmentation 1.2. Key questions answered in this study 1.3. Executive summary Chapter 2: Asia-Pacific machine learning market - market overview 2.1. Asia-Pacific market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 2.2. Asia-Pacific - market drivers and challenges 2.3. Value chain analysis – machine learning market 2.4. Porter’s five forces analysis 2.5. Market size- by components (software tools, cloud and web-based APIs and others) 2.5. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.5. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.5. c. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.6. Market size- by service (professional services and managed services) 2.6. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.6. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.7. Market size- by organization size (SMEs and large enterprises) 2.7. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.7. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.8. Market size- by application (BFSI, automotive, healthcare, government and others) 2.8. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.8. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.8. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.8. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 2.8. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 3: China machine learning market- market overview 3.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 3.2. China - market drivers and challenges 3.3. Market size- by components (software tools, cloud and web-based APIs and others) 3.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.3. c. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.4. Market size- by service (professional services and managed services) 3.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.5. Market size- by organization size (SMEs and large enterprises) 3.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.6. Market size- by application (BFSI, automotive, healthcare, government and others) 3.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 3.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 4: India machine learning market - market overview 4.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 4.2. India - market drivers and challenges 4.3. Market size- By components (software tools, cloud and web-based APIs and others) 4.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.3. c. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.4. Market size- by service (professional services and managed services) 4.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.5. Market size- by organization size (SMEs and large enterprises) 4.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.6. Market size- By application (BFSI, automotive, healthcare, government and others) 4.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 4.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 5: Japan machine learning market - market overview 5.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 5.2. Japan - market drivers and challenges 5.3. Market size- by components (software tools, cloud and web-based APIs and others) 5.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.3. c. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.4. Market size- by service (professional services and managed services) 5.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.5. Market size- by organization size ( SMEs and large enterprises) 5.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.6. Market size- by application (BFSI, automotive, healthcare, government and others) 5.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 5.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 6: South Korea machine learning market - market overview 6.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 6.2. South Korea- market drivers and challenges 6.3. Market size- by components (software tools, cloud and web-based APIs and others) 6.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.3. c. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.4. Market size- by service (professional services and managed services) 6.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.5. Market size- by organisation size (SMEs and large enterprises) 6.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.6. Market size- By application (BFSI, automotive, healthcare, government and others) 6.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 6.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 7: ANZ machine learning market - market overview 7.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 7.2. ANZ - market drivers and challenges 7.3. Market size- by components (software tools, cloud and web-based APIs and others) 7.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.3. c. Revenue of Others - Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.4. Market size- by service (professional services and managed services) 7.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.5. Market size- by organization size (SMEs and large enterprises) 7.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.6. Market size- by application (BFSI, automotive, healthcare, government and others) 7.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 7.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 8: Rest of Asia Pacific machine learning market - market overview 8.1. Market overview- market trends, market attractiveness analysis, geography-wise market revenue (USD) 8.2. Rest of Asia Pacific - market drivers and challenges 8.3. Market size- by components (software tools, cloud and web-based APIs and others) 8.3. a. Revenue from software tools- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.3. b. Revenue from cloud and web-based APIs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.3. c. Revenue of Others - Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.4. Market size- by service (professional services and managed services) 8.4. a. Revenue from professional services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.4. b. Revenue from managed services- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.5. Market size- by organisation size (SMEs and large enterprises) 8.5. a. Revenue from SMEs- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.5. b. Revenue from large enterprises- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.6. Market size- by application (BFSI, automotive, healthcare, government and others) 8.6. a. Revenue from BFSI- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.6. b. Revenue from automotive- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.6. c. Revenue from healthcare- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.6. d. Revenue from government- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations 8.6. e. Revenue from others- Historical (2015-2017) and forecasted (2018-2023) market size (USD Bn), key observations Chapter 9: Competitive landscape 9.1. Microsoft 9.1.a. Company snapshot 9.1.b. Product offerings 9.1.c. Growth strategies 9.1.d. Initiatives 9.1.e. Geographical presence 9.1.f. Key numbers 9.2. Google Inc. 9.2.a. Company snapshot 9.2.b. Product offerings 9.2.c. Growth strategies 9.2.d. Initiatives 9.2.e. Geographical presence 9.2.f. Key numbers 9.3. IBM Watson 9.3.a. Company snapshot 9.3.b. Product offerings 9.3.c. Growth strategies 9.3.d. Initiatives 9.3.e. Geographical presence 9.3.f. Key numbers 9.4. Amazon 9.4.a. Company snapshot 9.4.b. Product offerings 9.4.c. Growth strategies 9.4.d. Initiatives 9.4.e. Geographical presence 9.4.f. Key numbers 9.5. Baidu 9.5.a. Company snapshot 9.5.b. Product offerings 9.5.c. Growth strategies 9.5.d. Initiatives 9.5.e. Geographical presence 9.5.f. Key numbers 9.6. Intel 9.6.a. Company snapshot 9.6.b. Product offerings 9.6.c. Growth strategies 9.6.d. Initiatives 9.6.e. Geographical presence 9.6.f. Key numbers 9.7. Facebook 9.7.a. Company snapshot 9.7.b. Product offerings 9.7.c. Growth strategies 9.7.d. Initiatives 9.7.e. Geographical presence 9.7.f. Key numbers Chapter 10: Conclusion Chapter 11: Appendix 11.1. List of tables 11.2. Research methodology 11.3. Assumptions 11.4. About Netscribes Inc.

1 Microsoft 2 Google Inc. 3 IBM Watson 4 Amazon 5 Baidu 6 Intel 7 Facebook 8 Apple Inc.