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This project walks you on how to create a twitter sentiment analysis model using python. Twitter sentiment analysis is performed to identify the sentiments of the people towards various topics. For this project, we will be analysing the sentiment of people towards Pfizer vaccines. We will be using the data available on Kaggle to create this mach…
This is a python project that is used to identify hate speech in tweets. The dataset used to train the model is available on Kaggle and consists of labelled tweets where 1 indicates hate speech tweets and 0 indicates non-hate speech tweets.
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 is about creating a machine learning model that can predict the house value based on the given dataset. We use different machine learning algorithms such as linear regression, decision tree and random forest to train the model, and the model that gives the best performance is used to predict the house value for new data.
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 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.
This project is about creating a machine learning algorithm that can predict the quality of wine based on the given dataset. Different machine learning algorithms such as logistic regression, decision tree and random forest are used in this project.
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…
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 project demonstrates how to perform sentiment analysis using deep learning on Amazon product reviews dataset. The dataset used for the project is obtained from Kaggle and consists of nearly 3000 reviews of amazon users regarding various amazon Alexa products like Alexa echo, Alexa dot etc. Exploratory data analysis is performed on the datas…