Machine Learning – Introduction

Machine Learning – Introduction

What is machine learning?

Machine learning is a field of computer science which gives computer to learn from example through self-improvement and without being explicitly coded by programmer. In simple words, ML is a type of artificial intelligence that extracts patterns out of raw data by using an algorithm or method.  It is the most exciting technology in recent years.

ML is used in various tasks like fraud detection, predictive maintenance, portfolio optimization, automate task, clustering, sentiment analysis, image recognition, recommendation system and many more.

Prerequisites for Machine learning:

Reader should know basic python, python library like NumPy, Scikit-learn, Scipy, Matplotlib and seaborn. If these topics are new for you then we highly recommend you please go through Python for Data Science Tutorial.

Why Machine Learning?

Let’s understand it with an example, Think of a day when the sky is full of dark clouds and thunderstorms. The 1st thing that comes to your mind is, it’s going to rain today.

How did you know that it’s going to rain?

You know it because, in your life, whenever you have seen the sky behaving the same then it has rained, that’s what Machine Learning is all about.  

A machine is train to be learn from past experiences (data feed in) with respect to some class of tasks and it is performance in a given task improves with the experience.

Any technology user today has benefitted from machine learning. Facial recognition technology allows social media platforms to help users tag and share photos of friends. Optical character recognition (OCR) technology converts images of text into movable type. Recommendation engines, powered by machine learning, suggest what movies or television shows to watch next based on user preferences. Self-driving cars that rely on machine learning to navigate may soon be available to consumers. Risk analysis  for banking and finance industry. These all types of work is happening through machine learning.

Machine Learning Lifecycle:

Data Science process

What does it hold for the future?

Remember the robot helpers you saw in I, Robot? Imagine those in our day-to-day lives. Helping clean up our homes and generally making life even easier.

Traffic annoying you? How about you relaxed in the air conditioning of your car, and it took care of taking you to your destination? On its own?

Or how about as soon as you entered your doctor’s office, they have access to all your relevant medical details. Enabling them to provide you with a more personalized diagnosis?

Below image are few among hundreds of ways it makes our lives easier.

Future of machine learning
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