## How to install XGBoost on windows

Recently my mac book ran out of service while I was at the middle of learning “Machine Learning”. For emergency purpose I had to buy a low configured windows machine …

## Where to use which machine learning algorithm

Supervised Learning

Linear Regression = Linear model

Logistic regression = Classification

Decision Tree = Classification (Non-linear)

Neural networks = Linear model, Classification

Support vector machine = Linear model, Classification

Unsupervised Learning

K-Mean = Clustering

Principal …

## What is Logistic Regression?

TLDR: “Logistic regression is a classification algorithm. It classifies data into different classes.”

Suppose you have lot of emails in your inbox. However, your personal mail server does not have any email spam filtering system. …

## What is the meaning of theta in machine learning algorithms?

When you start to learn linear regression and Logistic regression you will come up with an equation. The equation will contain theta. You might be wondering what does this theta in machine learning mean.
A …

## What is reinforcement learning?

Reinforcement learning is one type of Machine learning. In a single sentence, in this learning process a machine learns using trial and error method. Here basically, we give the machine 2 instructions.

1. Try all …

## Machine Learning Interview Questions (Part 2)

This is 2nd part “Machine Learning Interview Questions”. To read the first part of this series, click here

###### What are the pros and cons (advantages and disadvantages) of Bayes’ Theorem?

Pros: 1. Bayes’ theorem is …

## Machine Learning Interview Questions (Part 1)

This the first part of machine learning interview question. You can also read second part of this series with more questions here:

Machine Learning Interview Question Part 2

Nearly all big tech companies have an

## Types of Machine Learning : Supervised and Unsupervised

When it’s time to learn “Machine Learning”, the first thing that you will hear is “Types of Machine Learning”. Because this is where you will begin to learn.

Based on learning algorithms, machines can learn …