10 Algorithms Machine Learning Engineers Need To Know About Posted on : Jul 20 - 2017

With the fast mechanization brought about by the technological revolution, the word manual is slowly getting lost amidst the crowd and will very soon completely vanish. As Big Data has whisked the tech industry, Machine Learning is gaining importance and has robustly handled huge amount of data making accurate predictions.

In an era of constant progress, we can only guess what astounding invention and discovery is to come next. The data-crunching machines that have been seamlessly executing the advanced techniques.

WHAT IS MACHINE LEARNING

Machine learning is a subset of the Artificial Intelligence, which is a broader term and concept. Where Artificial Intelligence aims to make computers smarter and intelligent, Machine Learning has come up with ways to do that. In short, it is application of Artificial Intelligence. With the use of algorithms, that iteratively learn from data, machine learning improves the functionality of computers without being explicitly programmed.

CATEGORIZATION OF MACHINE LEARNING ALGORITHMS

If you are a Data Scientist or a machine learning passionate, you can work your way around machine learning projects using categories in which the algorithms of machine learning have been broken down.

SUPERVISED LEARNING

Using a pre-defined set of “training examples”, the program is trained facilitating its ability to reach on conclusions when new data is fed. The program is trained until the desired level of accuracy is reached.

UNSUPERVISED LEARNING

The program is given a bunch of data and it has to detect pattern and relationship on its own. The system has to infer function to describe the pattern from the unclassified data.

REINFORCEMENT LEARNING

Here the system interacts with the environment and produces actions discovering errors or rewards. View More