# Exponential Smoothing

Exponential Smoothing is used to weight data from previous time periods with exponentially decreasing importance in the forecast. …

# An Introduction to Forecasting

Forecasting, the art or science of predicting the future, is used in the decision making process to help business people reach conclusions about buying, selling, producing, hiring and many other actions.
Time-series data are the data gathered on a given characteristic over a period of time at regular intervals. The technique…

# Assumptions of Linear Regression

Why is it important to understand the assumptions of Linear Regression..?

ANSCOMBE’S QUARTET

A set of four different data sets that look completely distinctive from each other but had the same regression line. [ y = 0.5x + 3 ]
They also had the same mean for both x and y…

# Conditional Probability

The concept of Conditional Probability forms the basis of Bayes Theorem. Bayes Theorem forms the concept of Naive Bayes Classifier.

A simple formulation of Conditional Probability

How do we read this above equation…?

Suppose we have two events A and B.
Finding out the probability of A, given that event B…

# Bayes’ Theorem

Conditional Probability forms the basis of Bayes’ Theorem.
The formula for Bayes’ Theorem

Let’s try to understand how do we derive the above formula,

Consider we have two events A and B.
And we have two conditions :
P ( A | B ) : probability of A given that B has…

# Autocorrelation

Correlation coefficient is a ratio which defines the relationship between two random variables.
For example, if we are trying to find a correlation between x and y variable. …

# Confused with Confusing Confusion Matrix…!!!

The first time I looked at a Confusion matrix I was actually confused. In Spite of learning it in the class almost every time, I could never get the knack of it.The words “True Positive”, “False Positive”, “Type I and Type II error” were always confusing.Finally …

# A Basic understanding to Support Vector Machine

As we all know Machine Learning consists of three types of learning; Supervised learning, Unsupervised learning, Reinforcement learning, and
Support Vector Machine or SVM lies in the category of Supervised learning.
SVM is a kind of supervised learning used for Classification and Regression analysis.

To understand how it helps in…

# The Wonders of Dimensionality Reduction : Singular Value Decomposition

Singular value decomposition is another efficient technique to reduce dimensions in a large data set.

If we have a data matrix, we can represent the input matrix as a product of three different matrices, generally represented as U, ∑, V.
This method is called as Singular value decomposition.

## Tulsipatro

Data Scientist - In - Progress

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