Machine learning is an artificial intelligence (AI) application which allows systems to automatically learn from experience and improve without being explicitly programmed.
This category of algorithms allows software applications to gain accuracy in predicting outcomes.
Machine learning focuses on the development of computer programs that can access data and use it for learning on their own.
We at Vsynergize Global help industries with large amounts of data to use machine learning.
Benefits of Machine Learning
The Vsynergize Global Machine Learning Advantages are
- Sophisticated pattern recognition.
- Intelligent decisions.
- Self modifying.
- Multiple iterations.
Where are Machine Learning used?
Finance
Healthcare
Energy & Utilities
Logistics
Retail & E-Comm
Manufacturing
Education
Why Vsynergize Global?
- Our machine learning applications go beyond the hype and actually grow smarter over time
- We have experince in both B2C & B2B machine learning applications
- Our exhaustive expertise in AI enables us to create robust machine learning applications
How Machine Learning Work
Old machine, new tricks
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Create data models
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Classification
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Clustering
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Supervised/Reinforced learning
Some of these Industry Use Cases are
Government agencies
Government agencies like public safety and utilities use machine learning as they have multiple sources of data that can be mined for insights, and also to detect fraud and minimize identity theft.
Financial services
Banks and financial institutions use machine learning technology to identify important insights in data, and to prevent fraud.
Marketing and sales
Retail is booming with websites recommending similar items based on previous purchases. Machine learning captures data, analyzes it and uses it to personalize a shopping experience or in implementing a marketing campaign.
Healthcare
Machine learning is being used widely in the healthcare industry, with the advent of wearable devices and sensors that can use data to assess a patient's health in real time.
Oil and gas
Machine learning is being used for finding new energy sources, analyzing minerals, predicting refinery sensor failure, streamlining oil distribution to make it more efficient and cost-effective.
Transportation
Analyzing data and identifying patterns and trends to make routes more efficient and predict potential problems is an important aspect of machine learning transportation organizations.
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