What is Machine Learning

          Machine Learning is one of the trending field in present technological era.It is actually a subset of Artificial intelligence(AI). Machine learning is used every where in today's world like robots,self driving cars,recommendation system,AI chatbots and several other technologies.Deep Learning is the trending part in machine learning

    Machine learning is an application of artificial intelligence (AI) that gives systems the power to automatically learn and improve from experience without being explicitly programmed.We are training the machines with the help of different training data sets.

Different types of Machine learning are-

1. Supervised Learning
2. Unsupervised Learning
3. Reinforcement Learning

Supervised Learning

         In this type of learning we are teaching the machine with labelled data and the machine arrives at a conclusion about the correlation of input and output data.Common example is house Price prediction.

Different Types of Supervised Learning

1.Regression

    Regression analysis is a form of predictive modelling technique based on the strong relation between a dependent and independent variable

Line of best fit refers to a line through a scatter plot of data points that best expresses the connection between those points. We generally  use the least squares method to arrive at an equation for the line

The least squares method is a statistical procedure to find the best fit line for a set of data points by minimizing the sum of the residuals of points from the plotted curve. Least squares regression method is used to predict the behavior of dependent variables.

2.Classification

    Classification is the kind of technique of identifying to which  group or category a new or unknown observation belongs.   This is done on the basis of a training data containing many observations. Classification models include linear models like Logistic Regression, SVM, and non-linear ones like K-NN, Kernel SVM, and Random Forests.It is a supervised learning method because as said we do this with known data.

Unsupervised Learning

    In this type of learning we provide the machine with unlabelled data and the machine learns from that data based on the similarities and dissimilarities .Common example is Cat-Dog classification

Types:

1.Clustering

    Clustering is the task of dividing the population or data points into a variety of groups such that data points within the same groups are more similar to other data points within the same group and dissimilar to the data points in other groups.

Reinforcement Learning

In Reinforcement Learning machine learns from previous experience and analyzing the surrounding environment .It is generally a action-reward process that means when the system take an action in the particular environment it will get a reward.The reward may be positive or negative and the ultimate of aim machine(or agent) is to maximize the reward and thus act accordingly with the environment properly.

Eg -: Ping-Pong game ,Robot in Amazon ware house,Alpha go

Now lets talk about the different steps involved in machine learning.

• Data collection
• Data cleaning and pre-processing
• Splitting the data into test and training set 
• Select and create the machine learning model suitable for the given data
• Train the model using the training set and change the parameters if  required
• Predict the output of the test set and analyse whether it has good accuracy
• Deploy the model

With this post we have given you a short introduction to the wide era of machine learning.This series is to be continued for the beginners to provide intuitions on the subfield of ML , concepts with proper algorithms and examples.