Data visualization and one hot encoding of Kaggle dataset. Model trained with random forest classifier

Flight fare perdicting model

Understand the learning process of RNNs and discover the LSTM network architecture. Solve problems and perform Natural Language Processing using sequences of data

A US-based housing company named Surprise Housing has decided to enter the Australian market. The company uses data analytics to purchase houses at a price below their actual values and flip them on at a higher price.

This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy

Implemented content-based and collaborative filtering recommendation systems using Python

Flask API serving a trained ML model to perform inferences over the input Json.

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

It uses basic concepts of Deep Learning to classify the Iris Dataset.

Using different technique to deal with Text Classification for Sentimental Analsysi from the a base TF-IDF encoding to pre-trained sentence embeddings.

Used libraries and functions as follows:

Life expectancy data processing

This project showcases an End-to-End ML Project on the Auto MPG dataset, where the main objective is to predict miles per gallon (MPG) of a car, based on its given attributes. This prediction would greatly help the designer engineers to understand what would be the expected MPG of their designed car and help them make suitable changes to deliver…

Use PySpark to predict the success of a terrorist attack using different machine learning approaches

This repository will help to address complex topics of machine learning such as clustering techniques, PCA and cross validation

University Project: building a random forest to predict loan defaults. This involves data processing, standardization, optimization, performance metrics, and model analysis.

Book price dataset analysis and modeling