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abel-keya

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Practical Statistics Learn how to apply inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models.

Multiple-Linear-Regression-Multivariate-Quantile-Regression-Ridge-Regression-Lasso-Regression-and

Multiple Linear Regression ,Multivariate Quantile Regression, Ridge Regression, Lasso Regression and Elastic Net Regression

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employee_promotion_recommender

A determines whether an employee is due for promotion based on the HR metrics

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Decision-trees-classification-Models-and-Support-Vector-Machines

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Project-Communicate-Data-Findings

Data Visualization Learn to apply sound design and data visualization principles to the data analysis process. Learn how to use analysis and visualizations to tell a story with data.

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Project-Wrangle-and-Analyze-Data

Data Wrangling Learn the data wrangling process of gathering, assessing, and cleaning data. Learn how to use Python to wrangle data programmatically and prepare it for deeper analysis.

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Project-Investigate-a-Dataset

earn the data analysis process of questioning, wrangling, exploring, analyzing, and communicating data. Learn how to work with data in Python using libraries like NumPy and Pandas.

K-nearest-neighbor-kNN-classifier-and-a-Naive-Bayes-classifier

This project involves Implementation of a K-nearest neighbor (kNN) classifier and a Naive Bayes classifier. After conducting the experiments the resulting metrics are calculated

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abel-keya/Project-Analyze-A-B-Test-Results

abel-keya

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