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Orkhan-Bakir

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Heart disease is one of the biggest causes of morbidity and mortality among the population of the world. Prediction of cardiovascular disease is regarded as one of the most important subjects in the section of clinical data science.

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In this Data Science project, you will see how to build a basic model of simple as well as content-based recommendation systems.

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Pfizer-Analysis

The dataset that I am using for the task of Pfizer vaccine sentiment analysis is downloaded from Kaggle, which was initially collected from Twitter when people were sharing their opinions about the Pfizer vaccine. Let’s start the task of Pfizer vaccine sentiment analysis by importing the necessary Python libraries and the dataset:

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Predicting Employee Attrition in Python.

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The Federation Internationale de Football Association (FIFA)

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Compare different models, fixing the imbalance problem, building the best model according to best metric and perform hyperparameter tuning for accuracy, using Logistic Regression, CatBoost Classifier and LightGBM algorithms.

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USA_Housing-Linear-Regression-ML-

Here we have data "USA Housing" , which I took from Kaggle.com. I statistically analyzed and also used Linear Regression analysis using Machine Learning and made predictions.

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Orkhan-Bakir/Heart-Disease-Prediction-with-ML.

Orkhan-Bakir

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