Machine Learning Industry: The Future of Business and Power to Learn and Predict

Machine learning industry data book covers machine learning, deep learning, natural language processing markets.

Global Machine Learning Industry data book is a collection of market sizing information & forecasts, competitive benchmarking analyses, macro-environmental analyses, and regulatory & technological framework studies. Within the purview of the database, all such information is systematically analyzed and provided in the form of presentations and detailed outlook reports on individual areas of research.

Access the Global Machine Learning Industry Data Book from 2023 to 2030, compiled with details by Grand View Research

Machine Learning Market Growth & Trends

The global machine learning market size is anticipated to reach USD 419.94 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to expand at a CAGR of 34.8% from 2023 to 2030. The market is experiencing continuous growth, driven by the increasing demand for AI-driven solutions across industries. It is expected to expand further as more organizations recognize the potential of machine learning and invest in its applications. The growing deployment of Edge AI is responsible for market growth. Edge AI reduces the reliance on cloud computing and provides faster response times, improved privacy, and bandwidth efficiency.

Numerous companies are using machine learning (ML) in various industries to boost productivity, streamline processes, and facilitate decision-making. ML is used for personalized product recommendations, demand forecasting, fraud detection, inventory management, and pricing optimization. For instance, Netflix, Inc., a U.S.-based media-streaming and video-rental company, uses machine learning to enhance the customer experience. The company has long been using machine learning algorithms to personalize its viewer recommendations. E-commerce firms like Amazon.com, Inc, a U.S.-based multinational technology company, also uses ML for recommendation to boost sales.

Developments such as fine-tuned personalization, hyper-targeting, search engine optimization (SEO), no-code environments, self-learning bots, and others are expected to impact the machine-learning landscape significantly. These developments are responsible for the continuous evolution of machine learning applications, driven by the demand for personalized experiences, improved website rankings, efficient marketing strategies, accessibility, and intelligent automation.

For instance, Google LLC has significantly advanced machine learning, specifically in computer vision. Google's research division, Google Research, has developed and deployed machine learning models such as the Inception series and the EfficientDet object detection model. These models have significantly enhanced the accuracy and performance of computer vision tasks, including image classification, object detection, and image segmentation.

Order your copy of the Free Sample of “Machine Learning Industry Data Book - Machine Learning, Deep Learning, Natural Language Processing Market Size, Share, Trends Analysis, And Segment Forecasts, 2023 - 2030” Data Book, published by Grand View Research

Deep Learning Market Growth & Trends

The global deep learning market size is expected to reach USD 526.7 billion by 2030, expanding at a CAGR of 33.5% from 2023 to 2030, according to a new report by Grand View Research, Inc. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and the adoption of Artificial Intelligence (AI) in customer-centric services is expected to propel the growth of the deep learning industry over the forecast period.

AI has evolved rapidly in recent years, enabling machines to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked numerous potential opportunities for machine learning and deep learning applications. Furthermore, AI-as-a-service such as virtual assistants has allowed smaller organizations to implement AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage SMEs and large enterprises to invest significantly in deep learning technology. Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and further deployed to obtain relevant insights for a more reliable decision-making process. For instance, organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.

Image and voice recognition are some of the leading applications in the deep learning industry. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to acquire language skills while interacting with people. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps companies provide relevant results and automatic descriptions related to images.

Natural Language Processing Market Growth & Trends

The global natural language processing market size is estimated to reach USD 439.85 billion by 2030, expanding at a CAGR of 40.4% from 2023 to 2030, according to a new study by Grand View Research, Inc. Machine learning is predicted to play a critical role in natural language processing (NLP) techniques, mostly in text analytics, as AI advances. In the future, unsupervised and supervised learning will enable machine-learning engines to undertake more in-depth assessments. According to their ongoing evolution, social media platforms are expected to play a superior role in business decisions. A company, for instance, can rely on several NLP tools to track customer evaluations, feedback, and comments about their business on social media platforms and in the news around the time of a quarterly report.

Factors such as increased usage of smart devices to facilitate smart environments boost market growth. Additionally, the demand for NLP technologies is expanding owing to the rising demand for sophisticated text analytics and increasing internet and connected device usage. In addition, NLP-based apps are increasingly being used across industries to enhance customer experience. Additional profitable market expansion potentials are anticipated due to rising healthcare sector investments. However, constraints in the development of NLP technology utilizing neural networks and complexity associated with the use of code-mixed language during the implementation of NLP solutions constrain the use of cloud-based services, which can create hindrances for market growth.

Companies with huge amounts of spoken or unstructured text data can effectively discover, collect, and analyze dark data issues to the growing pragmatic application of NLP. The usage of NLP is anticipated to increase in areas like semantic search and intelligent chatbots that need to comprehend user intent. The abundance of natural language technologies is expected to endure to shape the communication capability of cognitive computing and the expanding utilization of deep learning and unsupervised and supervised machine learning. Intelligent data for businesses to develop plans, NLP is essential for tracking and monitoring market intelligence reports.

Go through the table of content of Machine Learning Industry Data Book to get a better understanding of the Coverage & Scope of the study.

Machine Learning Industry Data Book Competitive Landscape

The market participants are implementing several organic and inorganic growth strategies, including new product launches, product modernizations, collaborations, corporate expansions, and acquisitions and mergers. Further, the companies are also focusing on developing new products and services with enhanced capabilities. For instance, In May 2022, Meta announced the launch of a new Al platform MyoSuite.

Key players operating in the Machine Learning industry are –

• Advanced Micro Devices, Inc. • Amazon Web Services, Inc. • Apple Inc. • ARM Ltd • Atomwise Inc. • Baidu Inc. • Clarifai Inc. • Enlitic Inc. • Google LLC • Hewlett Packard Enterprise Development LP • H2O.AI • HyperVerge • IBM Corporation • Inbenta Holdings Inc. • Intel Corporation • Just AI Limited • Linguamatics • Meta Platforms Inc. • Microsoft Corporation • NVIDIA Corporation • NetBase Quid Inc. • Oracle Inc. • SAP SE • SAS Institute Inc. • Sensely Inc. • SoundHound AI, Inc.