This is a python project for building a linear regression model that is used to predict used car prices from a given dataset using machine learning. The dataset used for this project is taken from Kaggle. For the complete video explanation, check out the following link.

This python project explains how to implement sentiment analysis using machine learning (SVM) on amazon Alexa reviews dataset.

This notebook will show you how to implement a deep leaning algorithm (LSTM) on the Amazon Alexa Reviews dataset

This notebook will show you how to perform exploratory data analysis on the Big Mart Sales dataset

In this notebook, we will be performing machine learning on the Big mart sales dataset

In this notebook, we will look at performing Exploratory Data Analysis on the Airbnb dataset available on Kaggle.

This code explains how to create and customize decision trees in python.

This code will help you to create and customize seaborn heatmaps using python.

This code explains how to create and customize bar charts using matplotlib library.

This code will help you to create and customize histograms using python.

This code explains how to create and customize word clouds in python.

This repository contains the code used in my tokenization tutorial video.

This code will help you to create and customize pie charts using python.

This code explains how to perform (Exploratory Data Analysis) EDA using python on the amazon Alexa dataset.

This project demonstrates how to perform exploratory data analysis on car price prediction dataset. The dataset is available on Kaggle and consists of various attributes related to the sales price of used ford cars. We will be performing Exploratory Data Analysis to understand this data and to find out which factors affect the sales price of use…

Implementing neural networks on the IMDB movie review dataset of 50k movie reviews

This project demonstrates how to create a sentiment analysis and machine learning model on the IMDB dataset

This project explains on how to build a machine learning algorithm for calculating the medical insurance costs. Check out my video on this topic for the complete video explanation.

This project demonstrates how to implement k-means clustering on unsupervised data. The dataset used here is the famous iris dataset. To see a complete video explanation on this topic, check out the attached link.

This python project explains on how to implement a supervised machine learning algorithm on the famous iris dataset. The different classifiers used in this project includes decision tree and k-nearest neighbors. For a complete explanation of this project, check out my video on this topic.