Machine Learning

 Famous Definition which i like:

A computer program / algorithm is said to be learning by itself if, the performance of doing a task increases with experience.


Types of Machine Learning:

1.Basis on Data

2.Basis on solution approach / category


Data:

Data can be either in a structured form or in unstructured form

Structured Data:

Data that is stored in a structured manner, where data will be present in the form of columns/headers.

this data can be in any of the artificial data formats mentioned below:

CSV, TSV, XML, JSON, YAML,DBMS,HDFS etc...

Unstructured Data:

This type of files does not follow a column or header based structure for storing the data, below are some of the examples

Audio, Video, Image,text  files etc...


Classification of structured Data:



1. Basis on Data: 

            Machine Learning techniques are applied on Structured data where as Deep Learning  techniques are applied over Unstructured data.

2. Basis on solution approach / category:

            a. Supervised Learning : In this type of Learning, the algorithm will be fed with possible input data that occurred in the past with its outputs (labelled data), based on which the algorithm will try to find some pattern or relation between input and output and predicts the output in the future for a given set of inputs.

            b. Unsupervised Learning: In Unsupervised learning the algorithm / program will be fed with data on which it needs to find some pattern automatically with out feeding any labelled data(hence the Unsupervised).

            c. Reinforcement Learning: It is a type of Unsupervised learning in which the algorithm tries to improve itself by auto correcting the false predictions it did previously.


Machine Learning approach is designed to think of a problem like human instead of traditional if else programming which fails to generalize the solution on a larger dataset.


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