My Experience in Machine Learning with Udacity, Part1

Starting with the Intro to Machine Learning

Passionate about Cognitive Computing research, and also Developer and Network Engineer, I was following some posts on the publications of BOCQUENET JPh’s blog, when I fall on the Udacity’s platform by the end of 2015.

So, I got that Machine Learning is a key field for Cognitive Computation and started to undertake by the beginning of 2016 (February) the Intro to Machine Learning program of Sebastian Thrun and Katie Malone.

This course teaches the Machine Learning process through the Eron financial fraud person of interest detection. We passed through the key Machine Learning algorithms functionalities and covered the essentials steps : Data transformation techniques, Data visualization, Training, and Evaluation.

I reproduced here the ML process provided by Sebastian and Katie at the end of the course (Lesson 15, Summary).

At the end of the course, I performed the final project you can find HERE (not reviewed). It consists in creating a Person Of Interest (POI) identifier to find persons who may have committed a financial fraud at Eron. In the repository, you will find my implementation and my responses to the project questions. I was surprised when analyzing data my model was able to innocent some big bosses with big salaries and bonuses who was previously designed as POI because of their situation (It is not reviewed but you could see things by yourself, for the review you should also undertake the Data Analyst nanodegree program).

I finally realize the importance of the field of Machine Learning and decided to continue with the Machine Learning Engineer Nanodegree program.

Now I did it, I am a Machine Learning Engineer. To follow the next part of my story with its more awesome contents, built on real life projects of the industry, please click on the Part2 link. You should find valuable reasons to try it, if you are doubtful.