Machine Learning

Machine learning (ML) is the process of teaching a computer system on how to make accurate predictions when fed data through the study of computer algorithms that improve automatically through experience. It is a method of data analysis that automates analytical model building

Introduction

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed from examples, data, and experience. Through enabling computers to perform specific tasks intelligently, machine learning systems can carry out complex processes by learning from data, rather than following pre-programmed rules. The learning that is being done is always based on some sort of observations or data, such as direct experience, or instruction. Machine learning is about learning to do better in the future based on what was experienced in the past. The primary goal of machine learning research is to develop general-purpose algorithms of practical value. Such algorithms should be efficient.

Application of Technology

Recent years have seen many advances in machine learning, which have raised its capabilities across a suite of applications. Many people now interact with systems based on machine learning every day, for example in image recognition systems, such as those used on social media; voice recognition systems, used by virtual personal assistants; and recommender systems, such as those used by online retailers. As the field develops further, machine learning promises to support potentially transformative advances in a range of areas, and the social and economic opportunities which follow could be significant.

Business Case Example

There are many examples of machine learning problems.

Given below are several examples:

Optical Character Recognition: Categorize images of handwritten characters by the letters represented
Face Detection: Find faces in images (or indicate if a face is present)
Spam Filtering: identify email messages as spam or non-spam
Topic Spotting: categorize news articles (say) as to whether they are about politics, sports, entertainment, etc.
Spoken Language Understanding: within the context of a limited domain, determine the meaning of something uttered by a speaker to the extent that it can be classified into one of a fixed set of categories
Medical Diagnosis: Diagnose a patient as a sufferer or non-sufferer of some disease
Customer Segmentation: Predict, for instance, which customers will respond to a particular promotion fraud detection: identify credit card transactions (for instance) which may be fraudulent in nature
Weather Prediction: Predict, for instance, whether or not it will rain tomorrow
Traffic Predictions: Using anonymized location data from smartphones, Google Maps (Maps) can analyze the speed of movement of traffic at any given time
Ridesharing Apps Like Uber: How do these apps determine the price of your ride? How do they minimize the wait time once you hail a car? How do these services optimally match you with other passengers to minimize detours? The answer to all these questions is ML.