Chapter 2. Let's Help Machines Learn

Machine learning, when you first hear it, sounds more like a fancy word from a sci-fi movie than the latest trend in the tech industry. Talk about it to people in general and their responses are either related to being generally curious about the concept or being cautious and fearful about intelligent machines taking over our world in some sort of Terminator-Skynet way.

We live in a digital age and are constantly presented with all sorts of information all the time. As we will see in this and the coming chapters, machine learning is something that loves data. In fact, the recent hype and interest in this field has been fueled by not just the improvements in computing technology but also due to exponential growth in the amount of data being generated every second. The latest numbers stand at around 2.5 quintillion bytes of data every day (that's 2.5 followed by 18 zeroes)!

Note

Fun Fact: More than 300 hours of video data is uploaded to YouTube every minute

Source: https://www-01.ibm.com/software/data/bigdata/what-is-big-data.html

Just take a deep breath and look around. Everything around you is generating data all the time, of all sorts; your phone, your car, the traffic signals, GPS, thermostats, weather systems, social networks, and on and on and on! There is data everywhere and we can do all sorts of interesting things with it and help the systems learn. Well, as fascinating as it sounds, let us start our journey on machine learning. Through this chapter we will cover:

• Understanding machine learning
• Algorithms in machine learning and their application
• Families of algorithms: supervised and unsupervised