# Collaborative Filtering

The recommendation system is prove to be very helpful in increasing revenue for big platforms like Netflix, YouTube, Amazon, Flipkart etc. Users are also introduced with items they like and they don't have to rigorously search for it. There is one method for recommendation system called Collaborative Filtering. It's of two types :- User-based collaborative … Continue reading Collaborative Filtering

# K Means cluster , Decision tree , SVM

K Means cluster This a unsupervised machine learning algorithm. It form data into K clusters. Cluster are formed by choosing centroid. At first random centroid is picked. Iterating the process until centroid changes no more. Decision Tree In this algorithm flowchart of decision is formed on basis of that prediction is done. Every feature chosen … Continue reading K Means cluster , Decision tree , SVM

# Machine Learning

Machine Learning is basically learning patterns and making prediction. There are basically two types of machine learning algorithms :- Supervised learningUnsupervised learning Supervised Learning In this type of machine learning algorithm we provide labels or target values. For example :- we give a picture of dog and also label it that it is dog. Unsupervised … Continue reading Machine Learning

# Regression

We are going to discuss :- Linear regressionPolynomial regressionMultivariate regression Linear Regression It is very simple machine learning algorithm. In this we try to fit a straight line on our data sample. y = m*x+c This algorithm finds best fit values for m and c which are slope and intercept of the line. PolynomialIt is … Continue reading Regression

# Conditional Probability

Probability means how likely an event can occur and conditional probability is how likely an event can occur given another event has already occurred. There is a dependence between the events. P(B/A) = P(A,B)/P(A) P(B/A) - Probability of B given A P(A,B) - Probability of both B and A P(A) - Probability of A For … Continue reading Conditional Probability

# Covariance And Correlation

Covariance It gives relation between two features or two random variables. It tells how one depends upon other. It could be positive or negative. Simple way to find covariance is to multiple variance of both the variables. Let's discuss this with an example then it will be more clear. Let a = [1,2,3,4,5,6,7,8,9] and b … Continue reading Covariance And Correlation

# Getting Started With Matplotlib

Data Visualization is very important part of data science. It helps to explain our data to others. It helps us in understanding our data well. Without data visualization it is difficult to get insights of the data. So let's get started with data visualization. Matplotlib is go to library for data visualization. Let do some … Continue reading Getting Started With Matplotlib