Today, more and more businesses are trying different approaches to make use of the Artificial Intelligence. Which leads them to the most promising and relevant area called Machine Learning. Machine Learning is becoming a very popular approach for processing the big data and there’s been increasing demand for professionals. That makes everyone curious to know more about it.
Before you join the bandwagon, it’s necessary to understand what is. By understanding what is, you are in a better position to wield its immense power and ultimately make it work for you.
Defining Machine Learning
So what is ? Most definitions you are likely to come across require extensive statistical background to understand. The assumption is before coming into the reader has a background in related topics. Such an assumption introduces a recursive problem, which we should clear right away with a simple, yet comprehensive definition of .
Machine learning is the ability of a computer to learn how to perform tasks without explicit programming. Through , a computer can, for instance, learn how to recognize millions of faces without being explicitly program to identify each individual face.
At this point, you might be wondering how makes it possible for a computer to carry out a task without an overt programming. After all, our definition of elevates a computer to a system capable of demonstrating intelligence. To quell any skepticism, let’s look at the nuts and bolts of from a bird’s eye view.
Machine Learning: Under The Hood
Numerous book volumes on the nuts of bolts of exist which speaks to the enormous amount of information on the topic. Any attempt to compress the information on the topic is a futile undertaking.
For that reason, we’re only going to concentrate on the core fundamentals of which are sufficient enough to understand what is.
Algorithms are fundamental to . Think of algorithms as a recipe. Like recipes, algorithms break down a process into a number of steps that can be expressed in computer code. Machine learning algorithms are special because they incorporate that allow a computer to make smart decisions when presented with a scenario.
Think of Google’s self-driving cars. These cars stop at stop signs, make turns on their own, and avoid hitting objects all on their own. No one could possibly program every event such a car might come across, yet, Google’s self-driving cars go about their jobs remarkably well.
That’s the power of algorithms in . The algorithm is meant to achieve a predefined goal. It makes decisions after receiving input from its environment. To be able to make the right decision, the algorithm must first of all be trained. The training involves providing the algorithm with categorized data sets that identify the desired outcomes. With large sets of these data, a machine learns how to achieve the right outcome such that when presented with uncategorized data, the algorithm achieves the desired level of accuracy. […]