Techniques used by Machines

To Learn

Machine and Learning?

Yes, you heard it right!

Machine these days are capable to learn, and what's more interesting is that they are doing a great job

But How?

Thanks to the wonders of computers

Machine learns in a similar ways as we human do

• with the help of Data

or

• without data.

With Data

• When the machine learns with the help of data set or guidance, the learning is called, Supervised Learning.

• Similar to humans, machines are instructed to generate certain output for input based on the learning techniques used. (Later)

Without Data

• When Machine Learns based on the technique only, with no external guidance, this is known as Unsupervised Learning.

Concepts

Learning System, input, output, tutor and all with diagram

• The components of a machine learning system mainly consists of,

  • Input (Can be data or instructions)

  • Algorithm (Technique used to Learn)

  • Output (The conclusion made by the machine)

  • Actuators and Sensors, included creates learning system

Techniques!

We all have our method to learn, so do these machines!

• PCA
• Random Forest
• SVM
• Neural Netoworks
• Naive Bayes
• KNN
• Kmeans
• Bagging boosting
• Kernel

• Everyone, among humans, uses certain methods to learn things.

• These techniques can differ with others.

• Similarly, Machines uses different techniques to learn based on the circumstances.

• Techniques used by Machines include,

  • Neural network

  • SVM

  • KNN

  • K-Means

  • And so on,