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

Create a machine learning pipeline, that categorizes disaster events.

Submissions and project work for the Udacity Data Scientist Nanodegree

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

Apply unsupervised learning techniques to identify customers segments.

Determine customer churn for a music streaming company

NLP classifier for disaster messages

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.

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

Data Science Project for Udacity's Data Scientist Program. Using Python in Jupyter Notebook.

Use unsupervised learning techniques to organize the general population into clusters, then use those clusters to see which of them comprise the main user base for the company.