Udacity Data Scientist Nanodegree
Objectives: learn the skills you need to perform well as a data scientist.
Term 1: Machine Learning for Data Scientists
Period: 27 November 2018 - 24 February 2019
Project 1: Supervised Learning.
Find Donors for the CharityML.
CharityML is a fictitious charity organization that provides financial support for people learning machine learning. In an effort to improve donor outreach effectiveness, an algorithm is build that best identifies potential donors. The goal will be to evaluate and optimize several different supervised learners to determine which algorithm will provide the highest donation yield.
Project 2: Deep Learning.
Create an Image Classifier.
In this project, an image classification application is implement using a a deep learning model on a dataset of images and the trained model is used to classify new images. First, develop code in a Jupyter notebook, second convert it into a python application that you will run from the command line of your system.
This project is the same as the final AI Programming with Python Nanodegree project.
Project 3: Unsupervised Learning.
Creating Customer Segments.
The data and design for this project is provided by Arvato Financial Services. Apply unsupervised learning techniques on demographic and spending data for a sample of German households. Preprocess the data, apply dimensionality reduction techniques, and implement clustering algorithms to segment customers with the goal of optimizing customer outreach for a mail order company.
Last update: 28 September 2019