Introduction to Machine learning:

What is Machine Learning?

Now a days Machine learning is the more weighted and costly topic to learn. In this post I would like to share my knowledge on machine learning. Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.

The main target of Machine learning is the development of computer programs that can teach themselves to grow and change when exposed to new data.

The machine learning process is very similar to data mining.The data mining process is also searches through the data which looks for the patterns. Similarly machine learning uses the data to detect the patterns and adjust the programs accordingly.



There are two types of Machine learning algorithms:

• Supervised
• Unsupervised

The Supervised algorithms can apply what has been learned in the past to new data.

Coming to the unsupervised algorithms can draw inferences from data-sets.

What does machine learning code do?

For short-term Machine learning is a massive field, with many different algorithms for solving many different problems.

Remember, it depends on the data that we have given to the machine learning code.
Coming to neural networks, which modifies their parameters automatically in response to the prepared stimuli and expected response.This property allows neural networks to produce many behaviors.

Using neural networks, we can keep the current state of the approximation.These builds a type of model. This model tells the system how to revert on the inputs given. These neural networks will process the data even if the inputs are not seen before.

The machine learning has the capability to react to inputs that have never been seen before - is one of the core tenets of many machine learning algorithms.

Keep reading. I will be discussing the difference between the supervised and unsupervised learning in featured posts.