Embark on a transformative "100 Days of Machine Learning" journey. This curated repository guides enthusiasts through a hands-on approach, covering fundamental ML concepts, algorithms, and applications. Each day, engage in theoretical insights, practical coding exercises, and real-world projects. Balance theory with hands-on experience.

An analysis of house prices in Beijing

Feature Engineering steps implemented in Google Colab with step-by-step view.

Engage in the critical phase of Exploratory Data Analysis (EDA) using the tools and techniques from Python to uncover patterns, spot anomalies, test hypotheses, and identify the main structures of your dataset.

Predicting Hotel Booking Cancellation with Machine Learning

Final project program DBA mitra Ruangguru X Studi Independen Bersertifikat Kampus Merdeka batch 2

An comprehensive data analysis of a particular market and its customers.

This repository contains resources and code examples related to Feature Engineering and Exploratory Data Analysis (EDA) techniques in the field of data science and machine learning.

👩🏻‍🍳🍽️Restaurant Success Prediction using ML

This research work summarized different machine learning algorithms to create models for predicting diabetes patients utilizing the Diabetes Dataset (PIDD) from the UCI repository. The classifiers were K-Nearest Neighbors, Naïve Bayes, Support Vector, Decision Tree, Random Forest, Logistic Regression and Ensemble Model using a voting classifier.

Heart Risk Level Predicting Regression Model & Web using Feature Engineering and Data Preprocessing 🐤

* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering *Accuracy score *Confusion matrix *Classification report