Machine learning is the subfield of computer science that "gives computers the ability to learn without being explicitly programmed"
Machine learning focuses on the development of computer programs that can change when exposed to new data .It is a method of data analysis that automates analytical model building using algorithms that iteratively learn from data. Researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new – but one that’s gaining fresh momentum.
While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development.
Few of the sectors that use Machine Learning extensively are below
- Financial services
- Health care
- Oil and gas
- Marketing and Sales
A popular use for machine learning today is pattern recognition because it can recognize many types of images. For instance, the US Postal Service uses machine learning for handwriting recognition.
The course involves training on
- Machine learning tasks like classification, regression and clustering
- Data exploration and dimension reduction
- Model development with machine learning algorithm
- Applying predictive models to massive datasets and powerful analysis
- Pattern reorganization
- Text mining
- Model assessment and scoring
- Performance Measures
Eligibility: Any Degree
Course Duration: 2 Months