Learning Python for Data Analysis and Visualization course finished!

It finally happened! Over 100 lectures course Learning Python for Data Analysis and Visualization on Udemy. Very good introduction to Data Science with Python language. Lots of useful outbound links for the further exploration. And lots of stuff to think about, like in which tasks one should choose Python and where to choose R.

Wine quality assessment app

Developing Data Products course, ninth and last in Coursera's Data Science Specialization, finished. As a course project, we had to build web-application with elements of machine learning. And then make a pitch presentation for that app. We were expected to use Shiny package and Shinyapps.io platform to publish our projects on the web.

I found an interesting dataset of Portugal wines' chemical characteristics and assessed quality in UCI repository. It gave me an idea that one can predict wine quality after chemical analysis.
Random Forest was chosen as a modelling tool. I hosted the model right on my github account:
https://github.com/Oleg-Davydov/winequality

And there you are! :)
https://laborant.shinyapps.io/winequality

Pitch presentation was restricted by five pages including the cover. I added a bit of humor in it :) Use right and left arrows on your keyboard to turn pages.
http://oleg-davydov.github.io/winequality/Rpresenter.html

Machines are learned!

It finally happened! Machine Learning course on Coursera finished. https://www.coursera.org/learn/machine-learning
Mixed feelings as after an excellent movie. It's great that the good guys have won, but it's very interesting what will happen next! :)

All lectures have been very engaging. I've watched many of them two or three times. Now I have a notebook full of lecture notes. Hope Andrew will eventually write a book which I will definitely buy.

All programming assignments were far from "annoying homework", but rather interesting little challenges and at the same time the continuation of lectures with many practical tips and tricks inside.

I'm proud to get maximum grade, 100%. As a course bonus, I've connected on LinkedIn with lots of my classmates from all around the world! My network has grown several times.

Want to say Thank You Very Much to our instructor, Andrew Ng, professor of Stanford University. That was an amazing experience!

Workout in a right way

Do you do physical exercises? Do you do it right? :)
Our course project in Practical Machine Learning course https://www.coursera.org/course/predmachlearn was about this topic. Several people put on an accelerometers and performed some exercises the right and the wrong way (consciously). So our task was to build the model to predict whether a person does barbell lifts correctly or incorrectly.
I used Random Forest and Gradient Boosting algorithms. RF has won in a Cross-Validation. Here is my report: http://oleg-davydov.github.io/PML_course_project/course_project.html

Traditionally, many thanks to our instructor Jeff Leek, professor of Johns Hopkins University!

Statistical Inference and Regression Models

That was different! Two new courses in Data Science Specialization on Coursera. Two courses of almost pure mathemathics. Pure pleasure! :) Many thanks to my instructor Brian Caffo, professor of Johns Hopkins University!
Even though these concepts are mostly familiar to me thanks to my alma mater, Moscow State University, it's very useful to see them again in combination with R language.

Machine Learning

Enrolled in Machine Learning course on Coursera.
https://www.coursera.org/learn/machine-learning/
The instructor is Stanford Professor and Coursera founder Andrew Ng! Looking forward for a very fun couple of months :)

R programming

Today I got a certificate of completion of the R programming course, the second course in Coursera Data Science Specialization. https://www.coursera.org/course/rprog
And again, with Distinction, 100% grade! :) Many thanks to the great instructor Roger Peng, professor from Johns Hopkins University!

Coursera Data Science Specialization

Just enrolled in my first online course. It's 'The Data Scientist’s Toolbox', the first part of Coursera's Data Science Specialization. https://www.coursera.org/course/datascitoolbox
Hope to refresh my math skills a little bit and get a closer look at R programming language.