The 6-jars of Machine Learning

“A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” — Tom Mitchell, Carnegie Mellon University

1. Data

The first jar of ML is “Data”. The internet is full of data, whatever site we go whatever we search we process data take this post as an example you are seeing data. The most common forms of data are: * Text * Image * Audio * Video (Mixture of audio and images)

In ML we use one or combination of different type of data. In order to learn from data we differentiate the data into two different sets i.e. input data (X) and Output data (Y).

I believe that we all are coming from technical background and we know the general definition of data. So why the data is first block of ML? The answer is very simple ML is something which learn from data and solve problem for....

2.Tasks

3. Model

4. Loss Function

5. Learning Algorithm

6. Evaluation

  1. First this
  2. Then a second thing
  3. Finally a third thing
  4. And so on

Wherever you go, there you are.