What is Machine Learning?

Learning, like intelligence, covers such a broad range of processes that it is difficult to define precisely. According to Wikipedia, Learning is the act of acquiring new or modifying and reinforcing existing knowledge, behaviors, skills, values, or preferences which may lead to a potential change in synthesizing information, depth of the knowledge, attitude or behavior relative to the type and range of experiences.

In Machine Learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.

Types of Learning

There are four types of learning methods in Machine Learning.

Classification, Regression and Clustering

Classification

The main goal of classification is to predict the target class (Yes/ No). If the trained model is for predicting any of two target classes. It is known as binary classification. Considering the student profile to predict whether the student will pass or fail. Considering the customer, transaction details to predict whether he will buy the new product or not. These kind problems will be addressed with binary classification. If we have to predict more the two target classes it is known as multi-classification. Considering all subject details of a student to predict which subject the student will score more. Identifying the object in an image. These kind problems are known as multi-classification problems.

Classification

Regression

The main goal of regression algorithms is the predict the discrete or a continues value. In some cases, the predicted value can be used to identify the linear relationship between the attributes. Suppose the increase in the product advantage budget will increase the product sales. Based on the problem difference regression algorithms can be used. some of the basic regression algorithms are linear regression, polynomial regression … etc

Regression

Clustering

Clustering is an unsupervised machine learning task that automatically divides the data into clusters, or groups of similar items. It does this without having been told how the groups should look ahead of time. As we may not even know what we’re looking for, clustering is used for knowledge discovery rather than prediction. It provides an insight into the natural groupings found within data.

Clustering

Machine Learning Books for Beginners

Programming Collective Intelligence: Building Smart Web 2.0 Applications

Programming Collective Intelligence, PCI as it is popularly known, is one of the best books to start learning machine learning. This book uses Python.

Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

This is a great introduction to Machine Learning using R.

Machine Learning in Action

Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis using Python.

Conclusion

ML Classes

I highly recommend reading Visual Introduction to Machine Learning.