Similar to the forest of real-life made of thousands of trees, Random Forest classifier is also made by combining multiple decision trees (not thousands).

Random forest is a supervised machine learning algorithm. The “forest” it builds, is an **ensemble** of decision trees, usually trained with the “**bagging**” method.

**First, we…**

The above example depicts the example of how we decide by looking at different parameters in our life. The same steps are followed in the decision tree classifier.

A Decision Tree is a simple representation for classifying examples. …

Hello Guys!!!

So far, we have discussed the Regression technique. Now, let us look at the second important Supervised learning algorithm, i.e. Classification.

Can classification problems be solved using Linear Regression? Why is Logistic Regression being a classification technique, still named regression?** **…

A brief introduction to Stepwise Regression.

So, you saw the name, and it says Stepwise. As the name stepwise regression suggests, this procedure selects variables in a step-by-step manner. Stepwise either adds the most significant variable or removes the least significant variable. …

What if your linear regression model cannot establish the relationship between the target variable and the predictor variable**?** In other words, what if they don’t have a linear relationship at all. After this blog, you will definitely get all your answers. This is my third blog on Regression series. …

We already learned Linear Regression, so what’s new here? What was the need for Ridge & Lasso Regression technique? We will be answering all these questions right here in detail. First: let’s look at possible categories of results that can be obtained from training a model with linear regression.

Whenever you come across linear regression, the first thing that should come to your mind is a scatter plot image somewhat like this.

To set up the possible **relationship **among different variables, various modes of statistical approaches are implemented, known as regression analysis. …

Hello everyone, as the title suggests, in this blog, we will be going through different types and processes involved in Machine Learning. But, let's first understand how machine learning works.

- The Machine Learning algorithm is trained using a training dataset and a model is created.
- Then the trained model works…

Python Pandas is an open-source library that provides high-performance data manipulation in Python. This tutorial is designed for both beginners and professionals.

- It’s fast and efficient DataFrame object indexing easy.
- Used for reshaping and pivoting of the data sets.
- Group by data for aggregations and transformations.
- It is used for…

In this blog, we will look at Python modules(NumPY & File Handling) necessary for Machine Learning. Please try to run the code by yourself for a better understanding.

Prerequisite; Basic knowledge of Python is necessary to understand this blog.

**NumPy**: NumPY is a Python library used for working with arrays…