Mediaboss Marketing

London, United Kingdom, Mon, 23 May 2022 11:12:07 / PhantMedia. / Global Machine Learning Market Fatpos Global anticipates the Machine Learning market to surpass USD 121.23 Billion by 2030; this is valued at 9.25 billion in 2020 at a compound annual growth rate of 37.5%.

Fatpos Global added new report into their database named Global Machine Learning MarketSegments: By Application: Advertising & media BFSI Government Healthcare Retail Telecom Utilities Manufacturing By Solution Type: Software Hardware Services 20212031 Global Industry Perspective, Comprehensive Analysis, and Forecast. The study offers historical data from 2016 to 2021, as well as a forecast for 2022 to 2031 based on revenue (USD Million).

Global Machine Learning Marketto surpass USD 121.23 Billion by 2030; this is valued at 9.25 billion in 2020 at a compound annual growth rate of 37.5%.

Global Machine Learning Market Summary:

Complete reportSample PDFCopy is ready: (Including List of Tables, Charts, Figures, TOC)published by Fatpos Global.

Global Machine Learning Market: Drivers and Restrains

Global Machine Learning Market: Segment Breakdown

The research report divides the market into segments based on region (country), manufacturer, product type, and application. During the forecast period of 2021 to 2031, each product type gives information on production. Consumption is also provided for the Application sector for the predicted period of 2021 to 2031. Understanding the segments aids in determining the importance of various market growth variables.

The Key Players mentioned in the Global Machine Learning MarketResearch Report include:

Competitive Landscape

Due to the vast number of players in this industry, the Global Machine Learning Market Market is highly consolidated. The research goes into great detail on these companies' present market position, previous performance, production and consumption trends, demand and supply graphs, sales networks, growth potential, and distribution methods. The study examines prominent market participants' strategic approaches to growing their product offerings and strengthening their market position.

Request a Discounton the Global Machine Learning Market Report (with COVID-19 Impact Study)

Exploring a Few Radical Features of the Global Machine LearningMarket Report:

Directly Get a Copy of the Report Global Machine Learning Market

Machine Learning Market Report Scope and Segmentation

Some of the key questions answered in this report:

About Us

Fatpos Global is a leading management consulting, advisory and market research organization that serves its clients globally through its team of experts and industry veterans that have years of expertise in management consulting, advisory and market research analysis. The organization functions across business consulting, strategy consulting, market research, operations consulting, financial advisory, human resources, risk & compliance, environmental consulting, software consulting, and sales consulting amongst others, and aims to aid businesses with bold decisions that help them embrace change for their sustainable growth.

Website:https://www.fatposglobal.com/

Mail:[emailprotected]

LinkedIn|Facebook|Instagram|Twitter|Pinterest

Follow this link:
Machine Learning 2021 Key Competitors, Major Products and Services, Share Analysis, and Upcoming Trends to 2030 - Digital Journal

The $20 million National Science Foundation award will help UAB and eight other Alabama-based universities build research infrastructure. UABs share will be about $2 million.

Yogesh Vohra Yogesh Vohra, Ph.D., is a co-principal investigator on a National Science Foundation award that will bring the University of Alabama at Birmingham about $2 million over five years.

The total NSF EPSCoR Research Infrastructure Improvement Program award of $20 million with its principal investigator Gary Zank, Ph.D., based at the University of Alabama in Huntsville will help strengthen research infrastructure at UAB, UAH, Auburn University, Tuskegee University, the University of South Alabama, Alabama A&M University, Alabama State University, Oakwood University, and the University of Alabama.

The award, Future technologies and enabling plasma processes, or FTPP, aims to develop new technologies using plasma in hard and soft biomaterials, food safety and sterilization, and space weather prediction. This project will build plasma expertise, research and industrial capacity, as well as a highly trained and capable plasma science and engineering workforce, across Alabama.

Unlike solids, liquids and gas, plasma the fourth state of matter does not exist naturally on Earth. This ionized gaseous substance can be made by heating neutral gases. At UAB, Vohra, a professor and university scholar in the UAB Department of Physics, has employed microwave-generated plasmas to create thin diamond films that have many potential uses, including super-hard coatings and diamond-encapsulated sensors for extreme environments. This new FTPP grant will support research into plasma synthesis of materials that maintain their strength at high temperatures, superconducting thin films and developing plasma surface modifications that incorporate antimicrobial materials in biomedical implants.

Vohra says the UAB Department of Physics will mostly use its share of the award to support faculty in the UAB Center for Nanoscale Materials and Biointegration and two full-time postdoctoral scholars, and support hiring of a new faculty member in computational physics with a background in machine-learning. The machine-learning predictions using the existing databases on materials properties will enable our research team to reduce the time from materials discovery to actual deployment in real-world applications, Vohra said.

The NSF EPSCoR Research Infrastructure Improvement Program helps establish partnerships among academic institutions to make sustainable improvements in research infrastructure, and research and development capacity. EPSCoR is the acronym for Established Program to Stimulate Competitive Research, an effort to level the playing field for states, territories and a commonwealth that historically have received lesser amounts of federal research and development funding.

Jurisdictions can compete for NSF EPSCoR awards if their five-year level of total NSF funding is less than 0.75 percent of the total NSF budget. Current qualifiers include Alabama, 22 other states, and Guam, the U.S. Virgin Islands and Puerto Rico.

Besides Alabama, the other four 2022 EPSCoR Research Infrastructure Improvement Program awardees are Hawaii, Kansas, Nevada and Wyoming.

In 2017, UAB was part of another five-year, $20 million NSF EPSCoR award to Alabama universities.

The Department of Physics is part of the UAB College of Arts and Sciences.

More:
NSF award will boost UAB research in machine-learning-enabled plasma synthesis of novel materials - University of Alabama at Birmingham

Research and innovation in machine learning in the power industry operations and technologies sector has declined in the last quarter but remains higher than it was a year ago.

The most recent figures show that the number of related patent applications in the industry stood at 108 in the three months ending March up from 103 over the same period in 2021.

Figures for patent grants related to followed a similar pattern to filings growing from 15 in the three months ending March 2021 to 19 in the same period in 2022.

The figures are compiled by GlobalData, which tracks patent filings and grants from official offices around the world. Using textual analysis, as well as official patent classifications, these patents are grouped into key thematic areas and linked to key companies across various industries.

Machine learning is one of the key areas tracked by GlobalData. It has been identified as being a key disruptive force facing companies in the coming years, and is one of the areas that companies investing resources in now are expected to reap rewards from. The figures also provide an insight into the largest innovators in the sector.

Siemens was the top innovator in the power industry operations and technologies sector in the latest quarter. The company, which has its headquarters in Germany, filed 83 related patents in the three months ending March. That was up from 77 over the same period in 2021.

It was followed by the Switzerland-based ABB with 11 patent applications, South Korea-based Korea Electric Power Corp (9 applications), and the US-based Honeywell International Inc (9 applications).

ABB has recently ramped up R&D in machine learning. It saw growth of 36.4% in related patent applications in the three months ending March compared to the same period in 2021 the highest percentage growth out of all companies tracked with more than 10 quarterly patents in the power industry operations and technologies sector.

See the article here:
Machine learning innovation among power industry companies dropped off in the last quarter - Power Technology

In a welcome move, the Indian Institute of Technology (IIT) has partnered with the online learning platform, Coursera. You can now access several courses from the comfort of your home while getting degrees certified by the premium institute.

Here are five courses that you may want to check out.

The course offers a strong foundation in business and technology. This is an opportunity to learn from industry experts at the B school. Dive into your area of specialisation, after choosing from over 55 electives. The curriculum spans business, management, data science and data analytics.

Eligibility criteria: A Bachelors degree with 65 per cent; four years of relevant work experience after graduation.Fees: Rs. 10,93,000/Duration: 24 months to 60 months

For more details, click here.

As algorithms shape our world and businesses, it is becoming more important to keep pace. In the course, you will gain exposure to the different algorithms that are needed for machine learning. You will also be trained in the application of Python programming in solving real-world financial problems.

Eligibility criteria: Knowledge of basic mathematics, linear algebra, calculus, statistics and spreadsheetsFees: Rs. 90,000/Duration: 6 months

For more details, click here.

Learn from industry experts who share with you their knowledge of mechatronics. In this course, you will be introduced to manufacturing processes and how these can be enhanced through computer technology. You will be trained in computer-aided design (CAD) and computer-aided manufacturing (CAM) softwares.

Eligibility criteria: Bachelors degree in any technology or engineering field; basic knowledge of programming. Students pursuing BE or BTech may also enrol.Fees: 1,12,500/Duration: 6 months

For more details, click here.

If you have been intrigued by the world of virtual reality, this course will help you delve deeper into understanding it. The course gives you a firm footing in the design and development of these technologies. Get expert insights into how to build deep learning models such as Encoder-Decoder.

Eligibility criteria: Bachelors degree in a related field with basic knowledge of programming.Fees: 1,12,500/Duration: 6 months

For more details, click here.

Understand the computational properties of Natural Language Processing with this course. Learn how to integrate machine learning and natural language processing to solve real-world problems across industries.

Eligibility criteria: Bachelors degree in a related field; a mathematics background in linear algebra, calculus, probability, statistics, data structures and algorithms; knowledge of Python.Fees: 1,12,500/Duration: 6 months

For more details, click here.

Link:
Machine Learning to Virtual Reality: Learn from Anywhere with 5 Online Courses by IITs - The Better India

PALO ALTO, Calif., May 23, 2022 (GLOBE NEWSWIRE) -- Anomalo, the complete data quality platform company, today announced support for Databricks, the Data and AI Company, to help customers build confidence in the data they use to make decisions and build products. Anomalo customers can now connect to their Databricks Lakehouse and start monitoring the quality of the data in any table, without writing code, configuring rules or setting thresholds.

A leader in the data warehousing and machine learning space, Databricks helps organizations streamline their data ingestion and management and make that data available for everything from business decision-making to predictive analytics and machine learning.

However, dashboards and data-powered products are only as good as the quality of the data that powers them. When scaling their data efforts, many companies quickly encounter one unfortunate fact: much of their data is missing, stale, corrupt or prone to unexpected and unwelcome changes. As a result, companies spend time dealing with issues in their data rather than unlocking that datas value and are at risk of silent failures in the data that might go undetected for months or more.

Anomalo addresses the data quality problem by monitoring enterprise data and automatically detecting and root-causing data issues, allowing teams to resolve any hiccups with their data before making decisions, running operations or powering models. Anomalo leverages machine learning to uncover a wide range of data failures with minimal human input. If desired, enterprises can fine-tune Anomalos monitoring through the no-code configuration of metrics and validation rules. This is in contrast to legacy approaches to monitoring data quality that require extensive work writing data validation rules or setting limits and thresholds.

Databricks customers can now begin monitoring the quality of their data with Anomalo in under five minutes. They simply connect Anomalos data quality platform to their Databricks account and select the tables they wish to monitor. No further configuration or code is required.

The Databricks Lakehouse Platform allows teams to unify their data engineering, analytics, and machine learning use cases all on a single platform. That makes Databricks a perfect partner in Anomalos vision of providing automated data quality monitoring for the entire enterprise, said Elliot Shmukler, co-founder and CEO of Anomalo.

Whether youre using your Databricks Lakehouse for analytics or machine learning and AI, your results are only as good as the quality of the underlying data. So, were excited to partner with Anomalo to give Databricks customers a great tool for automatically detecting and understanding the root-causes of data issues thus preventing such issues from leading to incorrect BI dashboards or broken machine learning models, said Roger Murff, VP, ISV Partners at Databricks.

Additional Resources

About AnomaloAnomalo helps enterprises build confidence in the data they use to make decisions and build products. Enterprises can simply connect Anomalos complete data quality platform to their data warehouse and begin monitoring their data in less than 5 minutes, all with minimal configuration and without a single line of code. Then, they can automatically detect and understand the root-cause of data issues, before anyone else. Anomalo is backed by Norwest Venture Partners, Foundation Capital, Two Sigma Ventures, Village Global and First Round Capital. For more information, visit https://www.anomalo.com/ or follow @anomalo_hq.

About Databricks Databricks is the data and AI company. More than 5,000 organizations worldwide including Comcast, Cond Nast, H&M, and over 40% of the Fortune 500 rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the worlds toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Media and Analyst Contact:Amber Rowlandamber@therowlandagency.com+1-650-814-4560

Read more:
Anomalo Integrates With Databricks to Help Enterprises Build Confidence in Their Data - GlobeNewswire