This reprositry contain all the codes of Udacity programming for data science course

Unsupervised ML: Finding Customer Segments in General Population

identifying target audience for a successful marketing campaign

Analysing the Boston AirBNB data for the Udacity Project and Blog Post

Unsupervised Machine Learning Project: Finding Customer Segments

Python application that scraps diverse sources for covid-19 papers, applies NLP transformations and stores them in a dataset for visualizing on a Flask web application.

Udacity Programming for Data Science using Python

Quick descriptive analysis of the Stack Overflow survey results dataset with focus on conditions conductive to higher job satisfaction

Submissions and project work for the Udacity Data Scientist Nanodegree

Create a machine learning pipeline, that categorizes disaster events.

Apply unsupervised learning techniques to identify customers segments.

NLP classifier for disaster messages

Determine customer churn for a music streaming company

Evaluate and optimize several different supervised learners to determine which algorithm will provide the highest donation yield while also reducing the total number of letters being sent.

Data, notes and solutions for Udacity's Data Scientist Nanodegree.

An an image classifier for species of flowers with PyTorch.

Web app to analyze disaster message into categories using data provided by Figure Eight

Build a CNN model to classify images of dogs according to their breed.

Analyze real census data and create a supervised machine learning model to predict potential donor for charity.

Image classifier using Pytorch