Machine Learning - Ability To Learn

 
Machine learning is a field of study in data science that gives computers the capability to learn without being exceptionally coded or programmed. It is among the most appealing technologies that one comes across in day to day life. As the phrase "ability to learn" indicates, it gives computers the ability to perform tasks on their own and makes them analogous to humans.
 
 
Now the question that arises in one's mind is, “What exactly does learning mean?”
 
When the computer is said to be learning it means it is learning from an experience in correspondence to some task, if the performance of the task improves with training .

How ML Works

  1. The first and foremost step in any data analysis is data collection . Collect the past data in a form that can be processed. The better the quality, the better the output. After data collection comes data processing.There might be a circumstance that the data collected is in raw form. So to use raw data we need to process it so that it can be understood by the machine.
  2. Once data is processed it is divided into training, cross-validation and testing sets. The division of data between these sets will be in the ratio 6:2:2.
  3. Consrtuct a model with suited algorithms and techniques using training data set.
  4. Now wetest our model on the test data set which was not provided at the time of training to check for precision, accuracy and recall.
 
Now if you are interested in exploring these technologies, you must fulfill the following prerequisites:
  • Linear Algebra
  • Statistics and Probability
  • Calculus
  • Graph Theory
  • Programming languages like Python,R or C++
So that’s it with the basics of machine learning. In thenext article we will discuss the type of machine learning techniques, examples and differences in machine learning with traditional programming.
 
So stay tuned and let me know what else you would like to know in the next articles.