Category Archives: Machine Learning

Machine Learning in Communication Market 2025:The latest research report published by Alexa Reports presents an analytical study titled as global Machine Learning in Communication Market 2020. The report is a brief study on the performance of both historical records along with the recent trends. This report studies the Machine Learning in Communication industry based on the type, application, and region. The report also analyzes factors such as drivers, restraints, opportunities, and trends affecting the market growth. It evaluates the opportunities and challenges in the market for stakeholders and provides particulars of the competitive landscape for market leaders.

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This study considers the Machine Learning in Communication value generated from the sales of the following segments:

The key manufacturers covered in this report: Breakdown data in in Chapter:- Amazon, IBM, Microsoft, Google, Nextiva, Nexmo, Twilio, Dialpad, Cisco, RingCentral

Segmentation by Type: Cloud-Based, On-Premise

Segmentation by Application: Network Optimization, Predictive Maintenance, Virtual Assistants, Robotic Process Automation (RPA)

The report studies micro-markets concerning their growth trends, prospects, and contributions to the total Machine Learning in Communication market. The report forecasts the revenue of the market segments concerning four major regions, namely, Americas, Europe, Asia-Pacific, and Middle East & Africa.

The report studies Machine Learning in Communication Industry sections and the current market portions will help the readers in arranging their business systems to design better products, enhance the user experience, and craft a marketing plan that attracts quality leads, and enhances conversion rates. It likewise demonstrates future opportunities for the forecast years 2019-2025.

The report is designed to comprise both qualitative and quantitative aspects of the global industry concerning every region and country basis.

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The report has been prepared based on the synthesis, analysis, and interpretation of information about the Machine Learning in Communication market 2020 collected from specialized sources. The competitive landscape chapter of the report provides a comprehensible insight into the market share analysis of key market players. Company overview, SWOT analysis, financial overview, product portfolio, new project launched, recent market development analysis are the parameters included in the profile.

Some of the key questions answered by the report are:

What was the size of the market in 2014-2019?What will be the market growth rate and market size in the forecast period 2020-2025?What are the market dynamics and market trends?Which segment and region will dominate the market in the forecast period?Which are the key market players, competitive landscape and key development strategies of them?

The last part investigates the ecosystem of the consumer market which consists of established manufacturers, their market share, strategies, and break-even analysis. Also, the demand and supply side is portrayed with the help of new product launches and diverse application industries. Various primary sources from both, the supply and demand sides of the market were examined to obtain qualitative and quantitative information.

Table of ContentsSection 1 Machine Learning in Communication Product DefinitionSection 2 Global Machine Learning in Communication Market Manufacturer Share and Market Overview2.1 Global Manufacturer Machine Learning in Communication Shipments2.2 Global Manufacturer Machine Learning in Communication Business Revenue2.3 Global Machine Learning in Communication Market Overview2.4 COVID-19 Impact on Machine Learning in Communication IndustrySection 3 Manufacturer Machine Learning in Communication Business Introduction3.1 Amazon Machine Learning in Communication Business Introduction3.1.1 Amazon Machine Learning in Communication Shipments, Price, Revenue and Gross profit 2014-20193.1.2 Amazon Machine Learning in Communication Business Distribution by Region3.1.3 Amazon Interview Record3.1.4 Amazon Machine Learning in Communication Business Profile3.1.5 Amazon Machine Learning in Communication Product Specification3.2 IBM Machine Learning in Communication Business Introduction3.2.1 IBM Machine Learning in Communication Shipments, Price, Revenue and Gross profit 2014-20193.2.2 IBM Machine Learning in Communication Business Distribution by Region3.2.3 Interview Record3.2.4 IBM Machine Learning in Communication Business Overview3.2.5 IBM Machine Learning in Communication Product Specification3.3 Microsoft Machine Learning in Communication Business Introduction3.3.1 Microsoft Machine Learning in Communication Shipments, Price, Revenue and Gross profit 2014-20193.3.2 Microsoft Machine Learning in Communication Business Distribution by Region3.3.3 Interview Record3.3.4 Microsoft Machine Learning in Communication Business Overview3.3.5 Microsoft Machine Learning in Communication Product Specification3.4 Google Machine Learning in Communication Business Introduction3.5 Nextiva Machine Learning in Communication Business Introduction3.6 Nexmo Machine Learning in Communication Business IntroductionSection 4 Global Machine Learning in Communication Market Segmentation (Region Level)4.1 North America Country4.1.1 United States Machine Learning in Communication Market Size and Price Analysis 2014-20194.1.2 Canada Machine Learning in Communication Market Size and Price Analysis 2014-20194.2 South America Country4.2.1 South America Machine Learning in Communication Market Size and Price Analysis 2014-20194.3 Asia Country4.3.1 China Machine Learning in Communication Market Size and Price Analysis 2014-20194.3.2 Japan Machine Learning in Communication Market Size and Price Analysis 2014-20194.3.3 India Machine Learning in Communication Market Size and Price Analysis 2014-20194.3.4 Korea Machine Learning in Communication Market Size and Price Analysis 2014-20194.4 Europe Country4.4.1 Germany Machine Learning in Communication Market Size and Price Analysis 2014-20194.4.2 UK Machine Learning in Communication Market Size and Price Analysis 2014-20194.4.3 France Machine Learning in Communication Market Size and Price Analysis 2014-20194.4.4 Italy Machine Learning in Communication Market Size and Price Analysis 2014-20194.4.5 Europe Machine Learning in Communication Market Size and Price Analysis 2014-20194.5 Other Country and Region4.5.1 Middle East Machine Learning in Communication Market Size and Price Analysis 2014-20194.5.2 Africa Machine Learning in Communication Market Size and Price Analysis 2014-20194.5.3 GCC Machine Learning in Communication Market Size and Price Analysis 2014-20194.6 Global Machine Learning in Communication Market Segmentation (Region Level) Analysis 2014-20194.7 Global Machine Learning in Communication Market Segmentation (Region Level) AnalysisSection 5 Global Machine Learning in Communication Market Segmentation (Product Type Level)5.1 Global Machine Learning in Communication Market Segmentation (Product Type Level) Market Size 2014-20195.2 Different Machine Learning in Communication Product Type Price 2014-20195.3 Global Machine Learning in Communication Market Segmentation (Product Type Level) AnalysisSection 6 Global Machine Learning in Communication Market Segmentation (Industry Level)6.1 Global Machine Learning in Communication Market Segmentation (Industry Level) Market Size 2014-20196.2 Different Industry Price 2014-20196.3 Global Machine Learning in Communication Market Segmentation (Industry Level) AnalysisSection 7 Global Machine Learning in Communication Market Segmentation (Channel Level)7.1 Global Machine Learning in Communication Market Segmentation (Channel Level) Sales Volume and Share 2014-20197.2 Global Machine Learning in Communication Market Segmentation (Channel Level) AnalysisSection 8 Machine Learning in Communication Market Forecast 2019-20248.1 Machine Learning in Communication Segmentation Market Forecast (Region Level)8.2 Machine Learning in Communication Segmentation Market Forecast (Product Type Level)8.3 Machine Learning in Communication Segmentation Market Forecast (Industry Level)8.4 Machine Learning in Communication Segmentation Market Forecast (Channel Level)Section 9 Machine Learning in Communication Segmentation Product Type9.1 Cloud-Based Product Introduction9.2 On-Premise Product IntroductionSection 10 Machine Learning in Communication Segmentation Industry10.1 Network Optimization Clients10.2 Predictive Maintenance Clients10.3 Virtual Assistants Clients10.4 Robotic Process Automation (RPA) ClientsSection 11 Machine Learning in Communication Cost of Production Analysis11.1 Raw Material Cost Analysis11.2 Technology Cost Analysis11.3 Labor Cost Analysis11.4 Cost OverviewSection 12 Conclusion

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Thus, Machine Learning in Communication Market serves as a valuable material for all industry competitors and individuals having a keen interest in the study.

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Trending now: Machine Learning in Communication Market Size, Share, Industry Trends, Growth Insight, Share, Competitive Analysis, Statistics,...

Global Data Science and Machine-Learning Platforms Market Size, Status and Forecast 2020-2026

This report studies the Data Science and Machine-Learning Platforms market with many aspects of the industry like the market size, market status, market trends and forecast, the report also provides brief information of the competitors and the specific growth opportunities with key market drivers. Find the complete Data Science and Machine-Learning Platforms market analysis segmented by companies, region, type and applications in the report.

New vendors in the market are facing tough competition from established international vendors as they struggle with technological innovations, reliability and quality issues. The report will answer questions about the current market developments and the scope of competition, opportunity cost and more.

The major players covered in Data Science and Machine-Learning Platforms Market: SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks, TIBCO Software, MathWorks, H20.ai, Anaconda, SAP, Google, Domino Data Lab, Angoss, Lexalytics, Rapid Insight, etc.

The final report will add the analysis of the Impact of Covid-19 in this report Data Science and Machine-Learning Platforms industry.

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Market Overview:-

Data Science and Machine-Learning Platforms market is segmented by Type, and by Application. Players, stakeholders, and other participants in the global Data Science and Machine-Learning Platforms market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2015-2026.

Data Science and Machine-Learning Platforms Market in its database, which provides an expert and in-depth analysis of key business trends and future market development prospects, key drivers and restraints, profiles of major market players, segmentation and forecasting. An Data Science and Machine-Learning Platforms Market provides an extensive view of size; trends and shape have been developed in this report to identify factors that will exhibit a significant impact in boosting the sales of Data Science and Machine-Learning Platforms Market in the near future.

This report focuses on the global Data Science and Machine-Learning Platforms status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Data Science and Machine-Learning Platforms development in United States, Europe, China, Japan, Southeast Asia, India, and Central & South America.

Market segment by Type, the product can be split into

Market segment by Application, split into

The Data Science and Machine-Learning Platforms market is a comprehensive report which offers a meticulous overview of the market share, size, trends, demand, product analysis, application analysis, regional outlook, competitive strategies, forecasts, and strategies impacting the Data Science and Machine-Learning Platforms Industry. The report includes a detailed analysis of the market competitive landscape, with the help of detailed business profiles, SWOT analysis, project feasibility analysis, and several other details about the key companies operating in the market.

The study objectives of this report are:

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The Data Science and Machine-Learning Platforms market research report completely covers the vital statistics of the capacity, production, value, cost/profit, supply/demand import/export, further divided by company and country, and by application/type for best possible updated data representation in the figures, tables, pie chart, and graphs. These data representations provide predictive data regarding the future estimations for convincing market growth. The detailed and comprehensive knowledge about our publishers makes us out of the box in case of market analysis.

Key questions answered in this report

Table of Contents

Chapter 1: Global Data Science and Machine-Learning Platforms Market Overview

Chapter 2: Data Science and Machine-Learning Platforms Market Data Analysis

Chapter 3: Data Science and Machine-Learning Platforms Technical Data Analysis

Chapter 4: Data Science and Machine-Learning Platforms Government Policy and News

Chapter 5: Global Data Science and Machine-Learning Platforms Market Manufacturing Process and Cost Structure

Chapter 6: Data Science and Machine-Learning Platforms Productions Supply Sales Demand Market Status and Forecast

Chapter 7: Data Science and Machine-Learning Platforms Key Manufacturers

Chapter 8: Up and Down Stream Industry Analysis

Chapter 9: Marketing Strategy -Data Science and Machine-Learning Platforms Analysis

Chapter 10: Data Science and Machine-Learning Platforms Development Trend Analysis

Chapter 11: Global Data Science and Machine-Learning Platforms Market New Project Investment Feasibility Analysis

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Data Science and Machine-Learning Platforms Market (impact of COVID-19) to See Massive Growth by 2026| SAS, Alteryx, IBM, RapidMiner, KNIME,...

The global COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market report is based on comprehensive analysis conducted by experienced and professional experts. The report mentions, factors that are influencing growth such as drivers, restrains of the market. The report offers in-depth analysis of trends and opportunities in the COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market. The report offers figurative estimations and predicts future for upcoming years on the basis of the recent developments and historic data. For the gathering information and estimating revenue for all segments, researchers have used top-down and bottom-up approach. On the basis of data collected from primary and secondary research and trusted data sources the report offers future predictions of revenue and market share.

The Leading Market Players Covered in this Report are : AIBrain,Amazon,Anki,CloudMinds,Deepmind,Google,Facebook,IBM,Iris AI,Apple,Luminoso,Qualcomm .

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Key Questions Answered in This Report:

Impact of Covid-19 in COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market:The utility-owned segment is mainly being driven by increasing financial incentives and regulatory supports from the governments globally. The current utility-owned COVID-19 Impact on Global Artificial Intelligence and Machine Learning are affected primarily by the COVID-19 pandemic. Most of the projects in China, the US, Germany, and South Korea are delayed, and the companies are facing short-term operational issues due to supply chain constraints and lack of site access due to the COVID-19 outbreak. Asia-Pacific is anticipated to get highly affected by the spread of the COVID-19 due to the effect of the pandemic in China, Japan, and India. China is the epic center of this lethal disease. China is a major country in terms of the chemical industry.

Key Businesses Segmentation of COVID-19 Impact on Global Artificial Intelligence and Machine Learning MarketOn the basis on the end users/applications,this report focuses on the status and outlook for major applications/end users, sales volume, COVID-19 Impact on Global Artificial Intelligence and Machine Learning market share and growth rate of COVID-19 Impact on Global Artificial Intelligence and Machine Learning foreach application, including-

On the basis of product,this report displays the sales volume, revenue (Million USD), product price, COVID-19 Impact on Global Artificial Intelligence and Machine Learning market share and growth rate ofeach type, primarily split into-

COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market Regional Analysis Includes: Asia-Pacific(Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia) Europe(Turkey, Germany, Russia UK, Italy, France, etc.) North America(the United States, Mexico, and Canada.) South America(Brazil etc.) The Middle East and Africa(GCC Countries and Egypt.)

Key Insights that Study is going to provide: The 360-degree COVID-19 Impact on Global Artificial Intelligence and Machine Learning market overview based on a global and regional level Market Share & Sales Revenue by Key Players & Emerging Regional Players Competitors In this section, various COVID-19 Impact on Global Artificial Intelligence and Machine Learning industry leading players are studied with respect to their company profile, product portfolio, capacity, price, cost, and revenue. A separate chapter on COVID-19 Impact on Global Artificial Intelligence and Machine Learning market Entropy to gain insights on Leaders aggressiveness towards market [Merger & Acquisition / Recent Investment and Key Developments] Patent Analysis** No of patents / Trademark filed in recent years.

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Table of Content:Global COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market Size, Status and Forecast 20261. Report Overview2. Market Analysis by Types3. Product Application Market4. Manufacturers Profiles/Analysis5. Market Performance for Manufacturers6. Regions Market Performance for Manufacturers7. Global COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market Performance (Sales Point)8. Development Trend for Regions (Sales Point)9. Upstream Source, Technology and Cost10. Channel Analysis11. Consumer Analysis12. Market Forecast 2020-202613. Conclusion

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COVID-19 Impact on Global Artificial Intelligence and Machine Learning Market Research Methodology: Business Plans, Inventive Technology, Growth...

Friday, June 26, 9am-10:30am Pacific time

Special Topic: Machine Learning & COVID-19: Time is of the Essence

Danilo Tomanovic will cover events including the 2003 SARS Epidemic & aspects of Machine Learning that can be applied to anticipate pandemic risk going forward. This presentation will offer a practical review of key dates & events during this COVID-19 pandemic and offer a fresh perspective on how we may collectively prevent this from happening again on this scale. For the audience this is an opportunity to become engaged as to what can work presently for them in preparation and anticipation of future concerns as they relate to viruses incorporating Machine Learning into their product/service designs.

Danilo Tomanovic's career includes sales, marketing, product development, global transaction banking, investment banking & risk management. He is the President, Founder of Machine Learning Deep Dive focused on creating ML Projects as proof of concepts pointed to market forces/demands.

This briefing will be followed by Q&A and our regular roundtable discussion.

At a Bootstrappers Breakfast(R) we have serious conversations about growing a business based on internal cashflow and organic profit: this is for founders who are actively bootstrapping a startup. We meet in the back room at several Silicon Valley restaurants so space is limited - Please RSVP. Join us upstairs for a little caffeine and sharing among the startup community.

Join other entrepreneurs who eat problems for breakfast.

* Compare Notes

* Exchange Ideas

* Learn from Others Mistakes

* Brainstorm with Peers

* Find Partners

* Small Group Atmosphere

* Serious Conversation

No Charge.

Presented by Bootstrappers Breakfast.

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Bootstrapper Breakfast: ML & COVID-19 -- Time is of the Essence - Patch.com

A new market report by Market Research Intellect on the Cloud Machine Learning Market has been released with reliable information and accurate forecasts for a better understanding of the current and future market scenarios. The report offers an in-depth analysis of the global market, including qualitative and quantitative insights, historical data, and estimated projections about the market size and share in the forecast period. The forecasts mentioned in the report have been acquired by using proven research assumptions and methodologies. Hence, this research study serves as an important depository of the information for every market landscape. The report is segmented on the basis of types, end-users, applications, and regional markets.

The research study includes the latest updates about the COVID-19 impact on the Cloud Machine Learning sector. The outbreak has broadly influenced the global economic landscape. The report contains a complete breakdown of the current situation in the ever-evolving business sector and estimates the aftereffects of the outbreak on the overall economy.

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The report also emphasizes the initiatives undertaken by the companies operating in the market including product innovation, product launches, and technological development to help their organization offer more effective products in the market. It also studies notable business events, including corporate deals, mergers and acquisitions, joint ventures, partnerships, product launches, and brand promotions.

Leading Cloud Machine Learning manufacturers/companies operating at both regional and global levels:

Sales and sales broken down by Product:

Sales and sales divided by Applications:

The report also inspects the financial standing of the leading companies, which includes gross profit, revenue generation, sales volume, sales revenue, manufacturing cost, individual growth rate, and other financial ratios.

The report also focuses on the global industry trends, development patterns of industries, governing factors, growth rate, and competitive analysis of the market, growth opportunities, challenges, investment strategies, and forecasts till 2026. The Cloud Machine Learning Market was estimated at USD XX Million/Billion in 2016 and is estimated to reach USD XX Million/Billion by 2026, expanding at a rate of XX% over the forecast period. To calculate the market size, the report provides a thorough analysis of the market by accumulating, studying, and synthesizing primary and secondary data from multiple sources.

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The market is predicted to witness significant growth over the forecast period, owing to the growing consumer awareness about the benefits of Cloud Machine Learning. The increase in disposable income across the key geographies has also impacted the market positively. Moreover, factors like urbanization, high population growth, and a growing middle-class population with higher disposable income are also forecasted to drive market growth.

According to the research report, one of the key challenges that might hinder the market growth is the presence of counter fit products. The market is witnessing the entry of a surging number of alternative products that use inferior ingredients.

Key factors influencing market growth:

Reasons for purchasing this Report from Market Research Intellect

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Customization of the Report:

Market Research Intellect also provides customization options to tailor the reports as per client requirements. This report can be personalized to cater to your research needs. Feel free to get in touch with our sales team, who will ensure that you get a report as per your needs.

Thank you for reading this article. You can also get chapter-wise sections or region-wise report coverage for North America, Europe, Asia Pacific, Latin America, and Middle East & Africa.

To summarize, the Cloud Machine Learning market report studies the contemporary market to forecast the growth prospects, challenges, opportunities, risks, threats, and the trends observed in the market that can either propel or curtail the growth rate of the industry. The market factors impacting the global sector also include provincial trade policies, international trade disputes, entry barriers, and other regulatory restrictions.

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Cloud Machine Learning Market 2019 Break Down by Top Companies, Countries, Applications, Challenges, Opportunities and Forecast 2026 - Cole of Duty

Through countless all-nighters studying for tests, soccer games and science fairs, William Tobin made the most of his four years in high school.

While Tobin earned recognition for his work on an individual basis, possibly his biggest achievement yet ties all of his work together as one. On May 27, it was announced Tobin has been named one of two U.S. Presidential Scholars for the entire state of West Virginia.

What it means to me to get it is really just its a culmination of everything Ive done in high school, said Tobin, who just graduated from Fairmont Senior High. The different national science fairs, countless hours of studying, the all-nighters Ive pulled, different competitions Ive went to, it really just brings all those together to just one award that recognizes it.

The Presidential Scholar program aims to recognize and reward high school seniors for achievements in test scores and extracurricular activities. Tobins extra-curricular resume is impressive having served as president of the West Virginia Association of Student Councils, vice president of the National Honor Society, vice president of Math Honors and captain of his schools math team.

Though this honor typically includes a trip to Washington, D.C., this year because of the coronavirus, the scholars will be awarded the Presidential Scholars Medallion, sponsored by the White House, and honored for their accomplishments during an online recognition event to ensure the health and safety of the award recipients.

Tobin plans to continue learning at Washington and Lee University, in Lexington City, Virginia, which will be aided by his full ride scholarship he earned as a U.S. Presidential Scholar.

I hope to study computer science and business at Washington & Lee University, Tobin said. After college, I hope to work a couple years in the industry, maybe with machine learning, then I hope to finally start a company with machine learning that combats issues.

Tobin thanks everyone he came in contact with at Fairmont Senior for their role in his high school career. He said he has good relationships with the faculty and administration at the school, having made his mark through his achievements.

He is a good student and an all around good kid, said James Greene, assistant principal at Fairmont Senior. I have dealt with Billy a number of times, and he is definitely worthy of the award, and I also think it goes to support the idea that Fairmont Senior is a top academic institution, and I think the teachers and students that we have here winning these kinds of awards reinforces that.

Greene said that Tobin is the first student at the school to get this award, at least in a while.

This is my sixth year here and I dont recall anyone else winning, Greene said. We have definitely had some high end academic students, but I think part of what separated Billy is his test scores. Getting a perfect ACT is very rare.

Along with tremendous academic success, Tobin played four years on the Polar Bears soccer team and contributed to the teams 2019 state championship in which they defeated Robert C. Byrd High 2-1 in sudden-death overtime. But head coach Darrin Paul said Tobins contributions to the team were not only on the field, but in the classroom with his teammates.

Billy was a great student and a great player, Paul said. He was always willing to help his teammates whether it was to become better players or help them with their homework after school.

Tobin was part of the team that took home the championship last year, which he also said was one of his biggest accomplishments.

Tobin said that even through the coronavirus pandemic, his motivation to pursue machine learning was not hindered. He said the isolation actually drove him to further expand his knowledge in the field.

I was pretty motivated to go into machine learning before this, Tobin said. Especially during this pandemic, Ive had a lot of free time, and I really tried to hone my interests into different types of machine learning.

Tobin also said he hopes to make a difference in situations like this pandemic, because machine learning can be used to study data to predict future events.

I think there will be a lot of different PhDs and dissertations done on this, especially in machine learning, Tobin said. Right now were collecting a bunch of data, but we dont really know what it means... Thats exactly what machine learning does, it looks at a bunch of data and tries to analyze trends.

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On the soccer field, or the classroom, William Tobin is a winner - Times-West Virginian