Machine Learning

Machine Learning is a subset of Artificial Intelligence (AI) that provides computers with the ability to learn without being explicitly programmed and to take intelligent decisions. It also enables machines to grow and improve with experiences.

It has various applications in science, engineering, finance, healthcare and medicine. Some applications of Machine Learning are given below.

Applications of Machine Learning:

·         Manufacturing

o    Predictive maintenance or condition monitoring

o    Warranty reserve estimation

o    Propensity to buy

o    Demand forecasting

o    Process optimization

o    Telematics

·         Retail

o    Predictive inventory planning

o    Recommendation engines

o    Upsell and cross-channel marketing

o    Market segmentation and targeting

o    Customer ROI and lifetime value

·         Healthcare and Life Sciences

o    Alerts and diagnostics from real-time patient data

o    Disease identification and risk stratification

o    Patient triangle optimization

o    Proactive health management

o    Healthcare provider sentiment analysis

·         Travel and Hospitality

o    Aircraft scheduling

o    Dynamic pricing

o    Social media-consumer feedback and interaction analysis

o    Customer complaint resolution

o    Traffic patterns and congestion management

·         Financial Services

o    Risk analytics and regulation

o    Customer Segmentation

o    Cross selling and up selling

o    Sales and marketing campaign management

o    Credit worthiness evaluation

·         Energy, Feedstock and Utilities

o    Power Usage analytics

o    Seismic data processing

o    Carbon emission and trading

o    Customer-specific pricing

o    Smart grid management

o    Energy demand and supply optimization

Advantages of Machine Learning-

·         Useful where large scale data is available

·         Large scale deployments of Machine Learning beneficial in terms of improved speed and accuracy

·         Understands non-linearity in the data and generates a function mapping input to output (Supervised Learning)

·         Recommended for solving classification and regression problems

·         Ensures better profiling of customers to understand their needs

·         Helps serve customers better and reduce attrition

And many more………

  • Machine learning in manufacturing
  • Machine learning in retail
  • Machine learning in healthcare and life sciences
  • Machine learning in travel and hospitality
  • Machine learning in financial services
  • Machine learning in energy, feedstock and utilities

Related Conference of Machine Learning

November 19-20, 2018

Global Expo on Computer Graphics & Animation

| Tokyo, Japan
November 22-23, 2018

9th World Congress on Optics, Photonics and Telecommunication

Bucharest | Romania
November 29-30, 2018

9th Euro Biosensors & Bioelectronics Congress

Dublin, Ireland
Jan 30-31, 2019

World Congress on Wireless Technology

Osaka , Japan
April 15-16, 2019

6th Global Meet on Wireless, Aerospace & Satellite Communications

| Amsterdam, Netherlands
June 10-11, 2019

3rd World Congress on Wind & Renewable Energy

Barcelona,Spain
June 20-21, 2019

Building Materials & Construction Technologies

| Stockholm, Sweden
September 16-17, 2019

8th International Conference on Biostatistics and Bioinformatics

San Francisco, USA
September 25-26, 2019 |

6th International Conference and Expo on Computer Graphics & Animation

Toronto | Ontario | Canada
October 14-15, 2019

6th World Machine Learning and Deep Learning Congress

Helsinki, Finland
October 23-24, 2019 |

12th International Conference & Exhibition on Biosensors & Bioelectronics

Vancouver | British Columbia | Canada

Machine Learning Conference Speakers

Recommended Sessions

Related Journals

Are you interested in