Machine Learning is an incredibly powerful tool. In the coming years, it promises to help solve some of our most pressing problems, as well as open up whole new worlds of opportunity.
Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
Computers 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.
Because of new computing technologies, machine learning today is not like machine learning of the past. 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.
Now it’s possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results. Machine learning provides high-value predictions that can guide better decisions and smart actions in real time without human intervention.
2 main machine learning methods are supervised learning and unsupervised learning.
Supervised learning – Historical labeled data is used to train Supervised learning is commonly used in applications where historical data predicts likely future events. For example, it can anticipate when credit card transactions are likely to be fraudulent or which insurance customer is likely to file a claim.
Unsupervised learning is used against data that has no historical labels. The goal is to explore the data and find some structure within. For example, it can find the main attributes that separate customer segments from each other. These algorithms are also used to segment text topics, recommend items and identify data outliers.
Use cases for Machine Learning-
- Email spam filtering.
- Knowing what customers are saying about you on Twitter
- Fraud detection
- Online recommendation offers like Amazon and Netflix
- Provides nearly instantaneous offers for other products that may interest you
- Provide near-real-time answers to your loan requests
- Real-time ads on web pages and mobile devices.
- Pattern and image recognition.
Few of the Machine Learning Algorithms –
- Support vector machines.
- K-means clustering.
- Neural networks.
- Decision trees
- Gradient boosting and bagging.