Machine Learning : Introduction

The field of study that gives computers the ability to learn without being explicitly programmed. – Arthur Samuel

It’s split into two broad ares :

  1. Supervised Machine Learning
  2. Unsupervised Machine Learning

Supervised Machine Learning : You feed the model with training data based on which it gives you the output (Feeding the model various pictures of cats and training it to recognise cats.)

Unsupervised Machine Learning : You feed the model with unstructured data and it makes sense of it and tries to structure it by creating clusters. (People you may know feature on Facebook.)

What is Reinforcement Learning?

In a nutshell it trains the algorithm based on a system of rewards and punishments. (Where the program wants to maximise its reward by interacting with the environment)


One of the Model for Machine Learning  : Inception v3

As per Apple’s website:¬†Inception v3 “Detects the dominant objects present in an image from a set of 1000 categories such as trees, animals, food, vehicles, people, and more.”


For beginners , its best to use one of the pre-trained models!

  • Learned how to use the Inception V3 CoreML model.
  • Let user click a photo or choose a photo from library.
  • The model then accesses the Photo and then prints the best / most accurate prediction.
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Prateek

Internet Marketer & Web Developer from New Delhi, India.

 

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