As we’ve come to know, data science is a vast domain wherein multiple processes are involved to arrive at the required answer. We have seen that statistics and math, which is one of the crucial components, is responsible for the analytics phase in data science. Now, once the analysis phase is over, the data takes a clearer form at which point it is ready to head into the modeling phase. As you would expect, this too involves performing several sub processes. But, at the heart of it all, the technology that is the primary impetus behind the whole modeling phase is machine learning.
What is machine learning? Machine learning is an application of artificial intelligence that enables computers to find patterns in the data and generate models based on them. When new data is provided to these models, they recognize the patterns and use them to help the computer make decisions autonomously. This way they can make decisions on their own without any need for explicit programming to carry out tasks.
Data scientists create a pipeline for data as it flows through their ML solution. This is a two-way iterative pipeline wherein each step of the pipeline is fed data from its preceding step.
The key stages of this pipeline are as follows:
ML algorithms are also broadly divided into two categories: supervised and unsupervised. We use supervised learning techniques when the value we want to predict is actually present in the dataset making the process of prediction simpler. On the other hand, unsupervised techniques are used when the required value is not present in the dataset. This scenario makes it a lot more challenging as the algorithm is tasked with finding hidden patterns as opposed to looking for something that is already present.
There are various techniques one can use to deploy learning techniques. Here are some popular examples that are preferred by most data scientists around the world.
Following the pattern of our previous article just like an ML algorithm, we have kept this introduction to another important component of data science short and sweet. Machine learning is arguably one of the most exciting prospects in technology. With a wide variety of applications ranging from medical diagnosis to market analysis, it is no doubt that machine learning will help mankind take the next step in furthering its evolution.
© 2019 THE TECHNOLOGY HEADLINES. ALL RIGHTS RESERVED.