Intro to Machine Learning with Tensorflow Nanodegree

I enrolled to Introduction to Machine Learning with Tensorflow Nanodegree when the pandemic started and Udacity offered one month trial to all its courses. Because I did not want to pay I only had one month to finish, so it was quite a challenge. Although I am quite familiar with the course content finishing all the projects in one month required a big effort.

This is a nanodegree includes the three aspects of Machine Learning; supervised learning, deep learning and unsupervised learning.

 

This Nanodegree has five parts and three projects.

Part 1 - Introduction to Machine Learning

Orientation part, to explain how the Nanodegree works.

Part 2 - Supervised Learning

In this part, supervised learning is discussed which is the most commonly used class of methods for model construction.

Project: Finding Donors Project
Part 3 - Deep Learning

In this part, foundations of neural network design and training in TensorFlow is discussed with an Image classifier project.

Project: Image Classifier Project
Part 4 - Unsupervised Learning

In this part, unsupervised learning methods is used to be used for unlabeled data originating from different kinds of problem domains.

Project: Identify Customer Segments
Part 5 - Congrats

End of the nanodegree with some extra stuff on Python.