This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Data fetched by wafers is to be passed through the machine learning pipeline and it is to be determined whether the wafer at hand is faulty or not apparently obliterating the need and thus cost of hiring manual labour.

Feature Engineering with Python

This is a beginner-level Data Science project carried out in the MCA I Semester, as a Data Visualization Project on topic Pollution Analysis in Indian States and Global Cities.

Processing of data gaps, coding of categorical features, data scaling.

Machine learning Classification for Family Determination for various generations by their age, height, weight, etc...

Showcasing data science skills for a dataset provided by State Farm for a coding interview.

Data imputation is used when there are missing values in a dataset. It helps fill in these gaps with estimated values, enabling analysis and modeling. Imputation is crucial for maintaining dataset integrity and ensuring accurate insights from incomplete data.

Build a model with machine learning to predict housing prices in Ames, Iowa. Top 11% in the Kaggle Housing Prices Competition.

Machine Learning course of Piero Savastano 5: ColumnTransformer, SimpleImputer, numpy

A machine learning project that predicts car prices based on a dataset.