DATANAYA
Machine Learning
It's here today, and here to stay.
Problem
Machine learning is the future and it's time to embrace it.
The human brain is great at recognizing patterns. Where teams of people would spend countless hours analyzing patterns, this can now be replaced by machine learning, to some degree.
Machine learning uses computational power to make inferences based on an assigned task – it's helping to solve many of the challenges facing us today.
Why do you need it? Because patterns provide valuable information about your business, your customers, and future growth.
The human brain is great at recognizing patterns. Where teams of people would spend countless hours analyzing patterns, this can now be replaced by machine learning, to some degree.
Machine learning uses computational power to make inferences based on an assigned task – it's helping to solve many of the challenges facing us today.
Why do you need it? Because patterns provide valuable information about your business, your customers, and future growth.
Use Cases
Financial services
Used by banks and the financial industry to identify important insights and prevent fraud.
These insights can qualify investment opportunities and help investors know when to trade, identify high-risk clients, and use cyber-surveillance to pinpoint warning signs of fraud.
Government
Government agencies such as public safety and utilities have a particular need for machine learning since they have multiple sources of data from which to pull insights.
Machine learning can analyze sensor data for ways to increase efficiency and save money, and help to detect fraud and minimize identity theft.
Health care
Machine learning is a fast-growing trend in the health care industry, thanks to the advent of wearable devices and sensors that use data to assess a patient's health in real time.
The technology can also help medical experts identify trends or red flags that may lead to improved diagnoses and treatment.
Marketing and sales
Machine learning allows websites to analyze buying history and promote items to customers that may be interested in, based on past purchases.
This ability to capture data, analyze it and use it to personalize a shopping experience (or implement a marketing campaign) is the future of retail.
Oil and gas
The number of machine learning use cases for this industry is vast and still expanding – finding new energy sources, analyzing minerals in the ground, predicting refinery sensor failure, and streamlining oil distribution to make it more efficient and cost-effective.
Transportation
The transportation industry relies on efficiency and predictability to increase profit. Machine learning helps delivery companies, public transportation and other transportation organizations identify patterns and trends that may impact routes or cause potential problems.
Used by banks and the financial industry to identify important insights and prevent fraud.
These insights can qualify investment opportunities and help investors know when to trade, identify high-risk clients, and use cyber-surveillance to pinpoint warning signs of fraud.
Government
Government agencies such as public safety and utilities have a particular need for machine learning since they have multiple sources of data from which to pull insights.
Machine learning can analyze sensor data for ways to increase efficiency and save money, and help to detect fraud and minimize identity theft.
Health care
Machine learning is a fast-growing trend in the health care industry, thanks to the advent of wearable devices and sensors that use data to assess a patient's health in real time.
The technology can also help medical experts identify trends or red flags that may lead to improved diagnoses and treatment.
Marketing and sales
Machine learning allows websites to analyze buying history and promote items to customers that may be interested in, based on past purchases.
This ability to capture data, analyze it and use it to personalize a shopping experience (or implement a marketing campaign) is the future of retail.
Oil and gas
The number of machine learning use cases for this industry is vast and still expanding – finding new energy sources, analyzing minerals in the ground, predicting refinery sensor failure, and streamlining oil distribution to make it more efficient and cost-effective.
Transportation
The transportation industry relies on efficiency and predictability to increase profit. Machine learning helps delivery companies, public transportation and other transportation organizations identify patterns and trends that may impact routes or cause potential problems.
Benefits
• Work more efficiently with large data sets
• Massive data consumption from unlimited sources
• Rapid analysis, prediction and processing
• Interpret past customer behavior at scale
• Massive data consumption from unlimited sources
• Rapid analysis, prediction and processing
• Interpret past customer behavior at scale
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- Toronto, ON M5V 2K4