世界各国のリアルタイムなデータ・インテリジェンスで皆様をお手伝い

機械学習の世界市場規模、シェア、動向、機会、予測。2018-2028年コンポーネント別(サービス&ソリューション)、企業規模別(中小企業、大企業)、展開別(クラウド、オンプレミス)、エンドユーザー別(医療、小売、IT・通信、自動車・交通、広告・メディア、BFSI、政府・防衛、その他)、地域別


Machine Learning Market Global Industry Size, Share, Trends, Opportunity, and Forecast. 2018-2028Segmented By Component (Services & Solutions), By Enterprises Size (SMEs and Large Enterprises), By Deployment (Cloud and On-premises), By End-User (Healthcare, Retailer, IT & Telecom, Automotive and Transports, Advertising & Media, BFSI, Government and Defense and Others), By Region

世界の機械学習市場は、予測期間2022-2028年に堅調なペースで成長すると予測されている。技術革新は、世界の機械学習市場の成長を支える重要な強みである。機械学習(ML)における人工知能(AI)により、コンピュ... もっと見る

 

 

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世界の機械学習市場は、予測期間2022-2028年に堅調なペースで成長すると予測されている。技術革新は、世界の機械学習市場の成長を支える重要な強みである。機械学習(ML)における人工知能(AI)により、コンピューター・プログラマーは明示的に訓練されることなく、より正確に結果を予測できるようになる。AIと機械学習は、開発とIT企業にとって最新の境界線である。機械学習は、与えられた一連のタスクの効率を高めるためにデータを使用する「学習」プロセスと方法の分析と開発に焦点を当てた研究分野である。
クラウドベースのサービスの採用が増加し、効果的なアウトプットが可能に
大量のデータを機械学習によって見直すことで、人が見過ごしてしまうような傾向やパターンを特定することができる。例えば、アマゾンのような電子商取引サイトでは、顧客の閲覧パターンや過去の購入履歴を知ることで、適切な商品や割引、リマインダーを提供することができる。さらに、機械学習はクラウド・コンピューティング・プラットフォームのServiceNowでも一部利用されている。ワークフローソフトウェアを提供する同組織は、機械学習を採用することで、顧客が面倒な手続きを可能な限り自動化し、スタッフが効率的に作業できるよう支援している。
人間が関与することなく業務を遂行できること、データセンターの機能が向上していること、高い計算能力があることなどが、この技術の台頭を後押ししている。さらに、SaaS(Software as a Service)、PaaS(Platform as a Service)、IaaS(Infrastructure as a Service)などの仮想サービスなど、多くの分野でクラウドベースの技術が急速に採用された結果、市場は拡大している。
機械学習は、失敗の特定とその軽減を可能にし、プロセスの標準化と進歩に直接影響する。エラーはプロセスの改善を可能にする。ミスと失敗を防ぐ能力に加えて、MLには在庫予測アルゴリズムがある。データから構築されたモデルは、いつエラーが発生するかを予測することができるため、エラーを未然に防ぐ対策が可能になる。これにより、市場は予測期間を通じて成長する可能性が高い。
自動運転車の最新動向と複数のハンドルデータセット
企業は機械学習能力を開発するために、このオープンソースの人工知能ライブラリーを利用している。例えば、TensorFlowは、企業がJavaプロジェクト、データフローグラフ、様々なアプリケーションを構築するために使用するライブラリである。Java用のAPIも存在する。例えば、アクセンチュア・コンサルタンシーやプロフェッショナル・サービス企業は、機械学習ベースの技術を使用しており、その市場規模は2,290億ドルに達している。このため、市場は予測期間中に成長すると予想される。
最近のモバイル・デバイスの多くは、サイクリングやランニングなど、ユーザーが特定の活動を行うと自律的に認識することができる。現在、初心者の機械学習エンジニアは、この種のプロジェクトの練習のために、慣性センサーを搭載したモバイル機器を使用して取得された数人のフィットネス活動記録からなるデータセットを利用している。さらに、将来の行動を的確に予測できる分類モデルも活用している。このため、データセット市場における機械学習の採用は、予測期間中に増加すると思われる。
MLは自動車分野でも導入されている。例えば、アメリカの多国籍企業であるテスラは、自動運転の開始を発表した。賛否両論を巻き起こしたが、自動運転車は機械学習で導入された最も顕著な進歩のひとつである。この市場は、予測期間中に高いCAGRで成長すると予想される。
機械学習市場は、機械学習-ロボットの統合によっても拡大している。例えば、統計年鑑 "World Robotics "によると、ロボットの設置台数は2018年に米国で新たな高みに達した。彼らはPIDアルゴリズムを使用したラインフォロワロボットを使用している。
熟練従業員の不足
しかし、機械学習をビジネスプロセスに組み込む際、ほとんどの組織が抱える主な困難は、分析の才能を持つ有資格者の不足であり、分析資料に目を光らせることのできる人材がさらに必要とされている。
市場の細分化
世界の機械学習市場は、コンポーネント、企業規模、展開、エンドユーザー、地域分布、競争環境に区分される。コンポーネントに基づき、市場はサービスとソリューションに区分される。企業規模に基づき、市場は中小企業と大企業に分けられる。展開に基づき、市場はクラウドとオンプレミスに分けられる。エンドユーザー別に見ると、ヘルスケア、小売、IT・通信、自動車・輸送、広告・メディア、BFSI、政府・防衛、その他に分けられる。
市場プレイヤー
世界の機械学習市場の主な市場プレイヤーは、Amazon Web Services, Inc.、Baidu, Inc.、Domino Data Lab, Inc.、Microsoft Corporation、Google, Inc.、Alpine Data、IBM Corporation、SAP SE、Intel Corporation、SAS Institute Inc.である。

最近の動向
- インドのNITI Aayogでは、糖尿病と心臓リスクの早期診断と特定にDNNモデルを使用することに取り組んでいる。また、FDAはヘルスケア分野でAIや機械知能を活用するための法的枠組みを策定中である。
- エヌビディアはハイエンドのゲームグラフィックスを提供しているが、AIと機械学習に賭ける同社の賭けは近年、実を結び始めている。
- ロンドンを拠点とするWayve社は、2022年1月に2億米ドルを調達した。その結果、企業は困難な運転状況に対応できる人工知能を訓練し、構築するための設備が整うことになる。
- アクセンチュアは世界有数のコンサルティング組織であり、テクノロジーの権威でもある。機械学習はアクセンチュアの様々な専門分野のひとつである。

レポートの範囲
本レポートでは、世界の機械学習市場を、業界動向に加えて、以下のカテゴリーに分類しています:
o 機械学習市場、コンポーネント別
o サービス
o ソリューション
o 機械学習市場:企業規模別
o 中小企業
o 大企業
o 機械学習市場:展開別
o クラウド
o オンプレミス
o 機械学習市場:エンドユーザー別
o ヘルスケア
o 小売業
o IT・通信
o 自動車・輸送
o 広告・メディア
o BFSI
o 政府・防衛
o その他
o 機械学習市場、地域別
o 北米
 米国
 メキシコ
 カナダ
o アジア太平洋
 インド
 日本
 韓国
 オーストラリア
 シンガポール
 マレーシア
 中国
ヨーロッパ
 ドイツ
 イギリス
 フランス
 イタリア
 スペイン
 ポーランド
 デンマーク
南米
 ブラジル
 アルゼンチン
 コロンビア
 ペルー
 チリ
中東
 南アラビア
 南アフリカ
 UAE
 イラク
 トルコ


競争状況
企業プロフィール:世界の機械学習市場に存在する主要企業の詳細分析。
利用可能なカスタマイズ
Tech Sci Research社は、与えられた市場データを用いて、世界の機械学習市場レポートにおいて、企業固有のニーズに応じたカスタマイズを提供しています。本レポートでは以下のカスタマイズが可能です:
企業情報
o 追加の市場参入企業(最大5社)の詳細分析とプロファイリング。

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目次

1. Service Overview
1.1. Market Definition
1.2. Scope of the Market
1.3. Markets Covered
1.4. Years Considered for Study
1.5. Key Market Segmentations
2. Research Methodology
2.1. Baseline Methodology
2.2. Key Industry Partners
2.3. Major Association and Secondary Sources
2.4. Forecasting Methodology
2.5. Data Triangulation & Validation
2.6. Assumptions and Limitations
3. Executive Summary
4. Voice of Customers
5. Global Machine Learning Market
5.1. Market Size & Forecast
5.1.1. By Value
5.2. Market Share & Forecast
5.2.1. By Component (Service and Solutions)
5.2.2. By Enterprise Size (SMEs and Large enterprises)
5.2.3. By Deployment (Cloud and On-premises)
5.2.4. By End-User (Healthcare, Retail, IT & Telecom, Automotive & Transports, Advertising & Media, BFSI, Government & Defense and Others)
5.2.5. By Region
5.3. By Company (2022)
5.4. Market Map
6. North America Machine Learning Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Component
6.2.2. By Enterprise Size
6.2.3. By Deployment
6.2.4. By End-Use
6.2.5. By Country
6.3. North America: Country Analysis
6.3.1. United States Machine Learning Market Outlook
6.3.1.1. Market Size & Forecast
6.3.1.1.1. By Value
6.3.1.2. Market Share & Forecast
6.3.1.2.1. By Component
6.3.1.2.2. By Enterprise Size
6.3.1.2.3. By Deployment
6.3.1.2.4. By End-Use
6.3.2. Canada Machine Learning Market Outlook
6.3.2.1. Market Size & Forecast
6.3.2.1.1. By Value
6.3.2.2. Market Share & Forecast
6.3.2.2.1. By Component
6.3.2.2.2. By Enterprise Size
6.3.2.2.3. By Deployment
6.3.2.2.4. By End-Use
6.3.3. Mexico Machine Learning Market Outlook
6.3.3.1. Market Size & Forecast
6.3.3.1.1. By Value
6.3.3.2. Market Share & Forecast
6.3.3.2.1. By Component
6.3.3.2.2. By Enterprise Size
6.3.3.2.3. By Deployment
6.3.3.2.4. By End-Use
7. Asia-Pacific Machine Learning Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Component
7.2.2. By Enterprise Size
7.2.3. By Deployment
7.2.4. By End-Use
7.2.5. By Country
7.3. Asia-Pacific: Country Analysis
7.3.1. China Machine Learning Market Outlook
7.3.1.1. Market Size & Forecast
7.3.1.1.1. By Value
7.3.1.2. Market Share & Forecast
7.3.1.2.1. By Component
7.3.1.2.2. By Enterprise Size
7.3.1.2.3. By Deployment
7.3.1.2.4. By End-Use
7.3.2. India Machine Learning Market Outlook
7.3.2.1. Market Size & Forecast
7.3.2.1.1. By Value
7.3.2.2. Market Share & Forecast
7.3.2.2.1. By Component
7.3.2.2.2. By Enterprise Size
7.3.2.2.3. By Deployment
7.3.2.2.4. By End-Use
7.3.3. Japan Machine Learning Market Outlook
7.3.3.1. Market Size & Forecast
7.3.3.1.1. By Value
7.3.3.2. Market Share & Forecast
7.3.3.2.1. By Component
7.3.3.2.2. By Enterprise Size
7.3.3.2.3. By Deployment
7.3.3.2.4. By End-Use
7.3.4. South Korea Machine Learning Market Outlook
7.3.4.1. Market Size & Forecast
7.3.4.1.1. By Value
7.3.4.2. Market Share & Forecast
7.3.4.2.1. By Component
7.3.4.2.2. By Enterprise Size
7.3.4.2.3. By Deployment
7.3.4.2.4. By End-Use
7.3.5. Australia Machine Learning Market Outlook
7.3.5.1. Market Size & Forecast
7.3.5.1.1. By Value
7.3.5.2. Market Share & Forecast
7.3.5.2.1. By Component
7.3.5.2.2. By Enterprise Size
7.3.5.2.3. By Deployment
7.3.5.2.4. By End-Use
7.3.6. Singapore Machine Learning Market Outlook
7.3.6.1. Market Size & Forecast
7.3.6.1.1. By Value
7.3.6.2. Market Share & Forecast
7.3.6.2.1. By Component
7.3.6.2.2. By Enterprise Size
7.3.6.2.3. By Deployment
7.3.6.2.4. By End-Use
7.3.7. Malaysia Machine Learning Market Outlook
7.3.7.1. Market Size & Forecast
7.3.7.1.1. By Value
7.3.7.2. Market Share & Forecast
7.3.7.2.1. By Component
7.3.7.2.2. By Enterprise Size
7.3.7.2.3. By Deployment
7.3.7.2.4. By End-Use
8. Europe Machine Learning Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Component
8.2.2. By Enterprise Size
8.2.3. By Deployment
8.2.4. By End-Use
8.2.5. By Country
8.3. Europe: Country Analysis
8.3.1. Germany Machine Learning Market Outlook
8.3.1.1. Market Size & Forecast
8.3.1.1.1. By Value
8.3.1.2. Market Share & Forecast
8.3.1.2.1. By Component
8.3.1.2.2. By Enterprise Size
8.3.1.2.3. By Deployment
8.3.1.2.4. By End-Use
8.3.2. United Kingdom Machine Learning Market Outlook
8.3.2.1. Market Size & Forecast
8.3.2.1.1. By Value
8.3.2.2. Market Share & Forecast
8.3.2.2.1. By Component
8.3.2.2.2. By Enterprise Size
8.3.2.2.3. By Deployment
8.3.2.2.4. By End-Use
8.3.3. France Machine Learning Market Outlook
8.3.3.1. Market Size & Forecast
8.3.3.1.1. By Value
8.3.3.2. Market Share & Forecast
8.3.3.2.1. By Component
8.3.3.2.2. By Enterprise Size
8.3.3.2.3. By Deployment
8.3.3.2.4. By End-Use
8.3.4. Russia Machine Learning Market Outlook
8.3.4.1. Market Size & Forecast
8.3.4.1.1. By Value
8.3.4.2. Market Share & Forecast
8.3.4.2.1. By Component
8.3.4.2.2. By Enterprise Size
8.3.4.2.3. By Deployment
8.3.4.2.4. By End-Use
8.3.5. Spain Machine Learning Market Outlook
8.3.5.1. Market Size & Forecast
8.3.5.1.1. By Value
8.3.5.2. Market Share & Forecast
8.3.5.2.1. By Component
8.3.5.2.2. By Enterprise Size
8.3.5.2.3. By Deployment
8.3.5.2.4. By End-Use
8.3.6. Poland Machine Learning Market Outlook
8.3.6.1. Market Size & Forecast
8.3.6.1.1. By Value
8.3.6.2. Market Share & Forecast
8.3.6.2.1. By Component
8.3.6.2.2. By Enterprise Size
8.3.6.2.3. By Deployment
8.3.6.2.4. By End-Use
8.3.7. Italy Machine Learning Market Outlook
8.3.7.1. Market Size & Forecast
8.3.7.1.1. By Value
8.3.7.2. Market Share & Forecast
8.3.7.2.1. By Component
8.3.7.2.2. By Enterprise Size
8.3.7.2.3. By Deployment
8.3.7.2.4. By End-Use
8.3.8. Denmark Machine Learning Market Outlook
8.3.8.1. Market Size & Forecast
8.3.8.1.1. By Value
8.3.8.2. Market Share & Forecast
8.3.8.2.1. By Component
8.3.8.2.2. By Enterprise Size
8.3.8.2.3. By Deployment
8.3.8.2.4. By End-Use
9. South America Machine Learning Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Component
9.2.2. By Enterprise Size
9.2.3. By Deployment
9.2.4. By End-Use
9.2.5. By Country
9.3. South America: Country Analysis
9.3.1. Brazil Machine Learning Market Outlook
9.3.1.1. Market Size & Forecast
9.3.1.1.1. By Value
9.3.1.2. Market Share & Forecast
9.3.1.2.1. By Component
9.3.1.2.2. By Enterprise Size
9.3.1.2.3. By Deployment
9.3.1.2.4. By End-Use
9.3.2. Argentina Machine Learning Market Outlook
9.3.2.1. Market Size & Forecast
9.3.2.1.1. By Value
9.3.2.2. Market Share & Forecast
9.3.2.2.1. By Component
9.3.2.2.2. By Enterprise Size
9.3.2.2.3. By Deployment
9.3.2.2.4. By End-Use
9.3.3. Colombia Machine Learning Market Outlook
9.3.3.1. Market Size & Forecast
9.3.3.1.1. By Value
9.3.3.2. Market Share & Forecast
9.3.3.2.1. By Component
9.3.3.2.2. By Enterprise Size
9.3.3.2.3. By Deployment
9.3.3.2.4. By End-Use
9.3.4. Peru Machine Learning Market Outlook
9.3.4.1. Market Size & Forecast
9.3.4.1.1. By Value
9.3.4.2. Market Share & Forecast
9.3.4.2.1. By Component
9.3.4.2.2. By Enterprise Size
9.3.4.2.3. By Deployment
9.3.4.2.4. By End-Use
9.3.5. Chile Machine Learning Market Outlook
9.3.5.1. Market Size & Forecast
9.3.5.1.1. By Value
9.3.5.2. Market Share & Forecast
9.3.5.2.1. By Component
9.3.5.2.2. By Enterprise Size
9.3.5.2.3. By Deployment
9.3.5.2.4. By End-Use
10. Middle East & Africa Machine Learning Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Component
10.2.2. By Enterprise Size
10.2.3. By Deployment
10.2.4. By End-Use
10.2.5. By Country
10.3. Middle East & Africa: Country Analysis
10.3.1. Saudi Arabia Machine Learning Market Outlook
10.3.1.1. Market Size & Forecast
10.3.1.1.1. By Value
10.3.1.2. Market Share & Forecast
10.3.1.2.1. By Component
10.3.1.2.2. By Enterprise Size
10.3.1.2.3. By Deployment
10.3.1.2.4. By End-Use
10.3.2. South Africa Machine Learning Market Outlook
10.3.2.1. Market Size & Forecast
10.3.2.1.1. By Value
10.3.2.2. Market Share & Forecast
10.3.2.2.1. By Component
10.3.2.2.2. By Enterprise Size
10.3.2.2.3. By Deployment
10.3.2.2.4. By End-Use
10.3.3. UAE Machine Learning Market Outlook
10.3.3.1. Market Size & Forecast
10.3.3.1.1. By Value
10.3.3.2. Market Share & Forecast
10.3.3.2.1. By Component
10.3.3.2.2. By Enterprise Size
10.3.3.2.3. By Deployment
10.3.3.2.4. By End-Use
10.3.4. Turkey Machine Learning Market Outlook
10.3.4.1. Market Size & Forecast
10.3.4.1.1. By Value
10.3.4.2. Market Share & Forecast
10.3.4.2.1. By Component
10.3.4.2.2. By Enterprise Size
10.3.4.2.3. By Deployment
10.3.4.2.4. By End-Use
11. Market Dynamics
11.1. Drivers
11.2. Challenges
12. Market Trends & Developments
13. Company Profiles
13.1. Amazon Web Services, Inc.
13.1.1. Business Overview
13.1.2. Key Revenue and Financials (If Available)
13.1.3. Recent Developments
13.1.4. Key Personnel
13.1.5. Key Product/Services
13.2. Baidu, Inc.
13.2.1. Business Overview
13.2.2. Key Revenue and Financials (If Available)
13.2.3. Recent Developments
13.2.4. Key Personnel
13.2.5. Key Product/Services
13.3. Domino Data Lab, Inc.
13.3.1. Business Overview
13.3.2. Key Revenue and Financials (If Available)
13.3.3. Recent Developments
13.3.4. Key Personnel
13.3.5. Key Product/Services
13.4. Microsoft Corporation
13.4.1. Business Overview
13.4.2. Key Revenue and Financials (If Available)
13.4.3. Recent Developments
13.4.4. Key Personnel
13.4.5. Key Product/Services
13.5. Google, Inc.
13.5.1. Business Overview
13.5.2. Key Revenue and Financials (If Available)
13.5.3. Recent Developments
13.5.4. Key Personnel
13.5.5. Key Product/Services
13.6. Alpine Data
13.6.1. Business Overview
13.6.2. Key Revenue and Financials (If Available)
13.6.3. Recent Developments
13.6.4. Key Personnel
13.6.5. Key Product/Services
13.7. IBM Corporation
13.7.1. Business Overview
13.7.2. Key Revenue and Financials (If Available)
13.7.3. Recent Developments
13.7.4. Key Personnel
13.7.5. Key Product/Services
13.8. SAP SE
13.8.1. Business Overview
13.8.2. Key Revenue and Financials (If Available)
13.8.3. Recent Developments
13.8.4. Key Personnel
13.8.5. Key Product/Services
13.9. Intel Corporation
13.9.1. Business Overview
13.9.2. Key Revenue and Financials (If Available)
13.9.3. Recent Developments
13.9.4. Key Personnel
13.9.5. Key Product/Services
13.10. SAS Institute Inc.
13.10.1. Business Overview
13.10.2. Key Revenue and Financials (If Available)
13.10.3. Recent Developments
13.10.4. Key Personnel
13.10.5. Key Product/Services
14. Strategic Recommendations
15. About Us & Disclaimer

 

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Summary

The Global Machine Learning Market is anticipated to grow at a robust pace in the forecast period 2022-2028. Technological innovation is the key strength behind the growth of the global machine-learning market. Artificial intelligence (AI) in machine learning (ML) enables computer programmers to forecast outcomes more accurately without being expressly trained. AI and machine learning are the newest boundaries for development and IT enterprises. Machine learning is an area of research focused on analyzing and developing "learning" processes and methods that use data to enhance efficiency on a given set of tasks.
Rising adoption of cloud-based services & ability to perform effectual output
Massive amounts of data can be reviewed by machine learning, which can identify trends and patterns that people would overlook. For instance, an e-commerce site like Amazon, knowing its customers' browsing patterns and past purchases, enables it to offer them the appropriate goods, discounts, and reminders. Furthermore, machine learning is used in part by ServiceNow, a cloud computing platform. The organization, which provides workflow software, employs machine learning to assist its clients in automating as many tedious procedures as possible and ensuring that staff members are working efficiently.
The ability to perform operations without involving human involvement, improvements in data center capabilities, and high computing power contribute to the technology's rise to prominence. Additionally, the market is expanding as a result of the quick adoption of cloud-based technologies in numerous sectors, such as Virtual services like software as a service (SaaS), platforms as a service (PaaS), and infrastructure as a service.
Machine Learning allows the identification of failures and their mitigation, directly affecting the standard and advancement of the process. Making errors enables process improvement. In addition to the ability for mistake and failure prevention, ML has stock prediction algorithms. Models built from data can forecast when an error may happen, enabling preventative measures to stop it from happening. This will likely cause the market to grow throughout the projected period.
Latest Trend of Self-Driving Vehicles and Multiple Handle Datasets
Companies are using this open-source artificial intelligence library to develop their machine-learning capabilities. For Instance, TensorFlow is library organizations use to build Java projects, data flow graphs, and various applications. APIs for Java are also present. For instance, Accenture Consultancy and professional services firms are using machine learning-based technologies with a market cap of USD 229 billion. Due to this market is expected to grow in the forecast period.
Many modern mobile devices can recognize autonomously when a user performs a certain activity, like cycling or running. Nowadays, novice machine learning engineers utilize a dataset that comprises fitness activity records for a few people that were acquired using mobile devices equipped with inertial sensors to practice with this sort of project. Furthermore, students are using categorization models that can precisely forecast future actions. Due to this, the adoption of machine learning in the datasets market is likely to increase in the forecast period.
ML is also being introduced in the automotive sector. For instance, Tesla, an American multinational company, announced the launch of self-driving. Although they have generated controversy, self-driving cars constitute one of the most remarkable advancements introduced in machine learning. This market is expected to grow with a high CAGR in the forecast period.
The machine-learning market has also expanded due to the integration of machine learning-in robots. For instance, Robot installations reached a new height in the United States in 2018, according to the statistics yearbook "World Robotics." Supporting they are using Line Follower Robot Using PID Algorithm due to which the Global machine learning market is expanding in the future.
Lack of skilled employees
However, the main difficulty most organizations have when integrating machine learning into their business processes is a lack of qualified workers with analytical talent, and there is an even greater need for those who can keep an eye on analytical material.
Market Segmentation
The Global Machine Learning Market is segmented into component, enterprise size, deployment, end-user, regional distribution, and competitive landscape. Based on components, the market is segmented into Services & Solutions. Based on enterprises size, the market is divided into SMEs and large enterprises. Based on deployment, the market is divided into cloud and on-premises. Based on end-user, the market is divided into healthcare, retailer, it & telecom, automotive and transports, advertising & media, BFSI, government and defense, and others.
Market player
The main market players in the Global Machine Learning Market are Amazon Web Services, Inc., Baidu, Inc, Domino Data Lab, Inc, Microsoft Corporation, Google, Inc, Alpine Data, IBM Corporation, SAP SE, Intel Corporation, and SAS Institute Inc.

Recent Developments
• The use of DNN models for the early diagnosis and identification of diabetes and cardiac risk is now being worked on by NITI Aayog in India. The FDA is also developing a legal framework for utilizing AI and machine intelligence in the healthcare sector.
• Nvidia provides high-end video game graphics best, but the company's gamble on AI and machine learning has begun to pay off in recent years.
• The London-based firm Wayve raised USD200 million in January 2022. As a result, enterprises will be better equipped to train and build artificial intelligence capable of handling challenging driving situations.
• Accenture is a leading worldwide consulting organization and technology authority that frequently assists businesses in using technology to alter their operations. Machine learning is one of Accenture's various specialties.

Report Scope:
In this report, Global Machine Learning Market has been segmented into the following categories, in addition to the industry trends, which have also been detailed below:
o Machine Learning Market, By Component:
o Services
o Solutions
o Machine Learning Market, By Enterprises Size:
o SMEs
o Large enterprises
o Machine Learning Market, By Deployment:
o Cloud
o On-premises
o Machine Learning Market, By End-user:
o Healthcare
o Retailer
o IT & telecom
o Automotive and Transports
o Advertising & Media
o BFSI
o Government and Defense
o Others
o Machine Learning Market, By Region:
o North America
 United States
 Mexico
 Canada
o Asia-Pacific
 India
 Japan
 South Korea
 Australia
 Singapore
 Malaysia
 China
o Europe
 Germany
 United Kingdom
 France
 Italy
 Spain
 Poland
 Denmark
o South America
 Brazil
 Argentina
 Colombia
 Peru
 Chile
o Middle East
 South Arabia
 South Africa
 UAE
 Iraq
 Turkey


Competitive Landscape
Company Profiles: Detailed analysis of the major companies present in the Global Machine Learning Market.
Available Customizations:
Global Machine Learning Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:
Company Information
o Detailed analysis and profiling of additional market players (up to five).



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Table of Contents

1. Service Overview
1.1. Market Definition
1.2. Scope of the Market
1.3. Markets Covered
1.4. Years Considered for Study
1.5. Key Market Segmentations
2. Research Methodology
2.1. Baseline Methodology
2.2. Key Industry Partners
2.3. Major Association and Secondary Sources
2.4. Forecasting Methodology
2.5. Data Triangulation & Validation
2.6. Assumptions and Limitations
3. Executive Summary
4. Voice of Customers
5. Global Machine Learning Market
5.1. Market Size & Forecast
5.1.1. By Value
5.2. Market Share & Forecast
5.2.1. By Component (Service and Solutions)
5.2.2. By Enterprise Size (SMEs and Large enterprises)
5.2.3. By Deployment (Cloud and On-premises)
5.2.4. By End-User (Healthcare, Retail, IT & Telecom, Automotive & Transports, Advertising & Media, BFSI, Government & Defense and Others)
5.2.5. By Region
5.3. By Company (2022)
5.4. Market Map
6. North America Machine Learning Market Outlook
6.1. Market Size & Forecast
6.1.1. By Value
6.2. Market Share & Forecast
6.2.1. By Component
6.2.2. By Enterprise Size
6.2.3. By Deployment
6.2.4. By End-Use
6.2.5. By Country
6.3. North America: Country Analysis
6.3.1. United States Machine Learning Market Outlook
6.3.1.1. Market Size & Forecast
6.3.1.1.1. By Value
6.3.1.2. Market Share & Forecast
6.3.1.2.1. By Component
6.3.1.2.2. By Enterprise Size
6.3.1.2.3. By Deployment
6.3.1.2.4. By End-Use
6.3.2. Canada Machine Learning Market Outlook
6.3.2.1. Market Size & Forecast
6.3.2.1.1. By Value
6.3.2.2. Market Share & Forecast
6.3.2.2.1. By Component
6.3.2.2.2. By Enterprise Size
6.3.2.2.3. By Deployment
6.3.2.2.4. By End-Use
6.3.3. Mexico Machine Learning Market Outlook
6.3.3.1. Market Size & Forecast
6.3.3.1.1. By Value
6.3.3.2. Market Share & Forecast
6.3.3.2.1. By Component
6.3.3.2.2. By Enterprise Size
6.3.3.2.3. By Deployment
6.3.3.2.4. By End-Use
7. Asia-Pacific Machine Learning Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Component
7.2.2. By Enterprise Size
7.2.3. By Deployment
7.2.4. By End-Use
7.2.5. By Country
7.3. Asia-Pacific: Country Analysis
7.3.1. China Machine Learning Market Outlook
7.3.1.1. Market Size & Forecast
7.3.1.1.1. By Value
7.3.1.2. Market Share & Forecast
7.3.1.2.1. By Component
7.3.1.2.2. By Enterprise Size
7.3.1.2.3. By Deployment
7.3.1.2.4. By End-Use
7.3.2. India Machine Learning Market Outlook
7.3.2.1. Market Size & Forecast
7.3.2.1.1. By Value
7.3.2.2. Market Share & Forecast
7.3.2.2.1. By Component
7.3.2.2.2. By Enterprise Size
7.3.2.2.3. By Deployment
7.3.2.2.4. By End-Use
7.3.3. Japan Machine Learning Market Outlook
7.3.3.1. Market Size & Forecast
7.3.3.1.1. By Value
7.3.3.2. Market Share & Forecast
7.3.3.2.1. By Component
7.3.3.2.2. By Enterprise Size
7.3.3.2.3. By Deployment
7.3.3.2.4. By End-Use
7.3.4. South Korea Machine Learning Market Outlook
7.3.4.1. Market Size & Forecast
7.3.4.1.1. By Value
7.3.4.2. Market Share & Forecast
7.3.4.2.1. By Component
7.3.4.2.2. By Enterprise Size
7.3.4.2.3. By Deployment
7.3.4.2.4. By End-Use
7.3.5. Australia Machine Learning Market Outlook
7.3.5.1. Market Size & Forecast
7.3.5.1.1. By Value
7.3.5.2. Market Share & Forecast
7.3.5.2.1. By Component
7.3.5.2.2. By Enterprise Size
7.3.5.2.3. By Deployment
7.3.5.2.4. By End-Use
7.3.6. Singapore Machine Learning Market Outlook
7.3.6.1. Market Size & Forecast
7.3.6.1.1. By Value
7.3.6.2. Market Share & Forecast
7.3.6.2.1. By Component
7.3.6.2.2. By Enterprise Size
7.3.6.2.3. By Deployment
7.3.6.2.4. By End-Use
7.3.7. Malaysia Machine Learning Market Outlook
7.3.7.1. Market Size & Forecast
7.3.7.1.1. By Value
7.3.7.2. Market Share & Forecast
7.3.7.2.1. By Component
7.3.7.2.2. By Enterprise Size
7.3.7.2.3. By Deployment
7.3.7.2.4. By End-Use
8. Europe Machine Learning Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Component
8.2.2. By Enterprise Size
8.2.3. By Deployment
8.2.4. By End-Use
8.2.5. By Country
8.3. Europe: Country Analysis
8.3.1. Germany Machine Learning Market Outlook
8.3.1.1. Market Size & Forecast
8.3.1.1.1. By Value
8.3.1.2. Market Share & Forecast
8.3.1.2.1. By Component
8.3.1.2.2. By Enterprise Size
8.3.1.2.3. By Deployment
8.3.1.2.4. By End-Use
8.3.2. United Kingdom Machine Learning Market Outlook
8.3.2.1. Market Size & Forecast
8.3.2.1.1. By Value
8.3.2.2. Market Share & Forecast
8.3.2.2.1. By Component
8.3.2.2.2. By Enterprise Size
8.3.2.2.3. By Deployment
8.3.2.2.4. By End-Use
8.3.3. France Machine Learning Market Outlook
8.3.3.1. Market Size & Forecast
8.3.3.1.1. By Value
8.3.3.2. Market Share & Forecast
8.3.3.2.1. By Component
8.3.3.2.2. By Enterprise Size
8.3.3.2.3. By Deployment
8.3.3.2.4. By End-Use
8.3.4. Russia Machine Learning Market Outlook
8.3.4.1. Market Size & Forecast
8.3.4.1.1. By Value
8.3.4.2. Market Share & Forecast
8.3.4.2.1. By Component
8.3.4.2.2. By Enterprise Size
8.3.4.2.3. By Deployment
8.3.4.2.4. By End-Use
8.3.5. Spain Machine Learning Market Outlook
8.3.5.1. Market Size & Forecast
8.3.5.1.1. By Value
8.3.5.2. Market Share & Forecast
8.3.5.2.1. By Component
8.3.5.2.2. By Enterprise Size
8.3.5.2.3. By Deployment
8.3.5.2.4. By End-Use
8.3.6. Poland Machine Learning Market Outlook
8.3.6.1. Market Size & Forecast
8.3.6.1.1. By Value
8.3.6.2. Market Share & Forecast
8.3.6.2.1. By Component
8.3.6.2.2. By Enterprise Size
8.3.6.2.3. By Deployment
8.3.6.2.4. By End-Use
8.3.7. Italy Machine Learning Market Outlook
8.3.7.1. Market Size & Forecast
8.3.7.1.1. By Value
8.3.7.2. Market Share & Forecast
8.3.7.2.1. By Component
8.3.7.2.2. By Enterprise Size
8.3.7.2.3. By Deployment
8.3.7.2.4. By End-Use
8.3.8. Denmark Machine Learning Market Outlook
8.3.8.1. Market Size & Forecast
8.3.8.1.1. By Value
8.3.8.2. Market Share & Forecast
8.3.8.2.1. By Component
8.3.8.2.2. By Enterprise Size
8.3.8.2.3. By Deployment
8.3.8.2.4. By End-Use
9. South America Machine Learning Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Component
9.2.2. By Enterprise Size
9.2.3. By Deployment
9.2.4. By End-Use
9.2.5. By Country
9.3. South America: Country Analysis
9.3.1. Brazil Machine Learning Market Outlook
9.3.1.1. Market Size & Forecast
9.3.1.1.1. By Value
9.3.1.2. Market Share & Forecast
9.3.1.2.1. By Component
9.3.1.2.2. By Enterprise Size
9.3.1.2.3. By Deployment
9.3.1.2.4. By End-Use
9.3.2. Argentina Machine Learning Market Outlook
9.3.2.1. Market Size & Forecast
9.3.2.1.1. By Value
9.3.2.2. Market Share & Forecast
9.3.2.2.1. By Component
9.3.2.2.2. By Enterprise Size
9.3.2.2.3. By Deployment
9.3.2.2.4. By End-Use
9.3.3. Colombia Machine Learning Market Outlook
9.3.3.1. Market Size & Forecast
9.3.3.1.1. By Value
9.3.3.2. Market Share & Forecast
9.3.3.2.1. By Component
9.3.3.2.2. By Enterprise Size
9.3.3.2.3. By Deployment
9.3.3.2.4. By End-Use
9.3.4. Peru Machine Learning Market Outlook
9.3.4.1. Market Size & Forecast
9.3.4.1.1. By Value
9.3.4.2. Market Share & Forecast
9.3.4.2.1. By Component
9.3.4.2.2. By Enterprise Size
9.3.4.2.3. By Deployment
9.3.4.2.4. By End-Use
9.3.5. Chile Machine Learning Market Outlook
9.3.5.1. Market Size & Forecast
9.3.5.1.1. By Value
9.3.5.2. Market Share & Forecast
9.3.5.2.1. By Component
9.3.5.2.2. By Enterprise Size
9.3.5.2.3. By Deployment
9.3.5.2.4. By End-Use
10. Middle East & Africa Machine Learning Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Component
10.2.2. By Enterprise Size
10.2.3. By Deployment
10.2.4. By End-Use
10.2.5. By Country
10.3. Middle East & Africa: Country Analysis
10.3.1. Saudi Arabia Machine Learning Market Outlook
10.3.1.1. Market Size & Forecast
10.3.1.1.1. By Value
10.3.1.2. Market Share & Forecast
10.3.1.2.1. By Component
10.3.1.2.2. By Enterprise Size
10.3.1.2.3. By Deployment
10.3.1.2.4. By End-Use
10.3.2. South Africa Machine Learning Market Outlook
10.3.2.1. Market Size & Forecast
10.3.2.1.1. By Value
10.3.2.2. Market Share & Forecast
10.3.2.2.1. By Component
10.3.2.2.2. By Enterprise Size
10.3.2.2.3. By Deployment
10.3.2.2.4. By End-Use
10.3.3. UAE Machine Learning Market Outlook
10.3.3.1. Market Size & Forecast
10.3.3.1.1. By Value
10.3.3.2. Market Share & Forecast
10.3.3.2.1. By Component
10.3.3.2.2. By Enterprise Size
10.3.3.2.3. By Deployment
10.3.3.2.4. By End-Use
10.3.4. Turkey Machine Learning Market Outlook
10.3.4.1. Market Size & Forecast
10.3.4.1.1. By Value
10.3.4.2. Market Share & Forecast
10.3.4.2.1. By Component
10.3.4.2.2. By Enterprise Size
10.3.4.2.3. By Deployment
10.3.4.2.4. By End-Use
11. Market Dynamics
11.1. Drivers
11.2. Challenges
12. Market Trends & Developments
13. Company Profiles
13.1. Amazon Web Services, Inc.
13.1.1. Business Overview
13.1.2. Key Revenue and Financials (If Available)
13.1.3. Recent Developments
13.1.4. Key Personnel
13.1.5. Key Product/Services
13.2. Baidu, Inc.
13.2.1. Business Overview
13.2.2. Key Revenue and Financials (If Available)
13.2.3. Recent Developments
13.2.4. Key Personnel
13.2.5. Key Product/Services
13.3. Domino Data Lab, Inc.
13.3.1. Business Overview
13.3.2. Key Revenue and Financials (If Available)
13.3.3. Recent Developments
13.3.4. Key Personnel
13.3.5. Key Product/Services
13.4. Microsoft Corporation
13.4.1. Business Overview
13.4.2. Key Revenue and Financials (If Available)
13.4.3. Recent Developments
13.4.4. Key Personnel
13.4.5. Key Product/Services
13.5. Google, Inc.
13.5.1. Business Overview
13.5.2. Key Revenue and Financials (If Available)
13.5.3. Recent Developments
13.5.4. Key Personnel
13.5.5. Key Product/Services
13.6. Alpine Data
13.6.1. Business Overview
13.6.2. Key Revenue and Financials (If Available)
13.6.3. Recent Developments
13.6.4. Key Personnel
13.6.5. Key Product/Services
13.7. IBM Corporation
13.7.1. Business Overview
13.7.2. Key Revenue and Financials (If Available)
13.7.3. Recent Developments
13.7.4. Key Personnel
13.7.5. Key Product/Services
13.8. SAP SE
13.8.1. Business Overview
13.8.2. Key Revenue and Financials (If Available)
13.8.3. Recent Developments
13.8.4. Key Personnel
13.8.5. Key Product/Services
13.9. Intel Corporation
13.9.1. Business Overview
13.9.2. Key Revenue and Financials (If Available)
13.9.3. Recent Developments
13.9.4. Key Personnel
13.9.5. Key Product/Services
13.10. SAS Institute Inc.
13.10.1. Business Overview
13.10.2. Key Revenue and Financials (If Available)
13.10.3. Recent Developments
13.10.4. Key Personnel
13.10.5. Key Product/Services
14. Strategic Recommendations
15. About Us & Disclaimer

 

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