機器學習：主題智能

Machine Learning - Thematic Intelligence

出版日期: 2022年12月07日 | 出版商:

GlobalData | 英文 76 Pages | 訂單完成後即時交付

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

簡介目錄

機器學習是人工智能 (AI) 的一個子集，它允許計算機系統在不明確編程的情況下從數據中學習和改進。機器學習是目前被企業採用的AI最實際的應用領域。

公司可以使用無代碼/低代碼和 MLaaS（機器學習即服務）平台來滿足沒有廣泛編程技能的人的需求，而不是從頭開始僱用程序員和設計機器學習工具。你可以設計一個適合的系統。因此，機器學習操作 (MLOps) 在以高標準實施和監控系統方面變得越來越普遍。

這家總部位於美國的機器學習公司在過去十年中通過 3,038 筆風險融資交易籌集了總計 579.6 億美元的資金。

在這份報告中，我們分析了全球機器學習 (ML) 的技術和市場趨勢，概述了該技術、主要應用領域、近期技術發展和引進趨勢、整體市場規模趨勢，我們正在調查相關專利申請和註冊趨勢，細分趨勢（硬件、軟件（大數據管理、機器學習技術）、服務（平台、MLaaS、圖書館）等）。

內容

執行摘要
市場進入者
技術概覽
趨勢
技術趨勢
宏觀經濟趨勢
監管趨勢
行業分析
市場規模和增長率預測
併購 (M&A)
風險投資
專利趨勢
公司申請趨勢
招聘趨勢
用例
時間表
價值鏈
硬件
軟件
服務
公司
部門記分卡
應用軟件記分卡
雲服務記分卡
詞彙表
參考文獻
主題研究的分析方法
關於全球數據
聯繫人

簡介目錄

Product Code: GDTMT-TR-S379

Machine learning is a subset of artificial intelligence (AI) that allows computer systems to learn and improve from data without being explicitly programmed. Machine learning is the most practical application of AI currently available for enterprise adoption.

Key Highlights

GlobalData forecasts the global AI market will be worth $136 billion in 2026. Specialist AI applications will account for the largest proportion of 2026 revenue at 37%, followed by AI consulting and support services at 30%. AI platforms will record the fastest revenue growth between 2021 and 2026 (a CAGR of 18%).
Instead of companies employing programmers to design machine learning tools from scratch, nocode/low-code and machine learning as a service (MLaaS) platforms allow those without extensive programming ability to design systems tailored to their needs. This has also led to the popularity of machine learning operations (MLOps) to ensure systems are implemented and monitored to a high standard.
AI is increasingly involved in life-changing decisions like welfare payments, mortgage approvals, and medical diagnoses. Consequently, transparency and explainability have become essential. Some key AI frameworks driving transparency in the sector include IBM's open-source AI 360 tool kit and Rulex's Logic Leaning Machine (LLM).
The main areas driving AI M&A deals are NLP, automated driving, MLaaS, and enterprise predictive analytics.
US-based machine learning companies have raised a total of $57,960 million through 3,038 venture financing deals in the last 10 years.

Scope

This report provides an overview of the machine learning theme.
It identifies the key trends impacting growth of the theme over the next 12 to 24 months.
It includes a comprehensive industry analysis, including market size and growth forecasts for AI hardware, AI platforms, AI consulting and support services, and specialized AI applications.
The detailed value chain breaks down machine learning into three areas: hardware, software (big data management and machine learning techniques), and services (platforms, MLaaS, and libraries).

Reasons to Buy

Machine learning will benefit all enterprises in some capacity, with potential advantages including automation, trend and pattern recognition, process improvement, and forecasting. This report will help readers make sense of the machine learning theme, understand training techniques and leading algorithms, the business benefits, identify the leading vendors and startups, and understand MLaaS, MLOps, and machine learning libraries.