Second Quarter Summary [Personal PhD Update #2.5]

 The second quarter of my Personal PhD has concluded and its time to look at what I have accomplished.
Highlight: I finished the Machine Learning Coursera course by Andrew Ng on time on the last day of the quarter!
 Lowlight: I wasn’t consistent with studying regularly and there was a period of 3 weeks where I didn’t do anything for the ML course.
Below follows how I did against my plan for the second quarter.

Computer Science track

DONE. Even though the book was published in 2007 and by tech book standards that’s like ancient, I still think its the best intro to Machine Learning for people who have absolutely no idea about Machine Learning. I am just saying this because I was ready to write this book off before even looking at it, but then by  my colleague’s recommendation I still read it. The book helped me to see how Machine Learning fits among other analysis methods. For example I have seen k-means clustering before being applied to bioinformatics data, but nobody called it a Machine Learning method. Turns out the same k-means clustering method used for prediction in a different community is now called a Machine Learning method.
I highly recommend reading the book before or slightly ahead of the Coursera ML course. Get general intuition from the book and then get mathematical intuition in the Coursera course.
Score: 1.0 out of 1.0.
2. Do rest of the Machine Learning course by Andrew Ng on Coursera (Weeks 6-11)
DONE. With Thanksgiving and Christmas holidays I totally procrastinated on the Coursera’s course. On weekends and holidays I am usually totally disconnected, so unfortunately it is not an opportunity to spend more time on Personal PhD. For Thanksgiving I went on an epic roadtrip from San Francisco to Mohave to Grand Canyon to Sedona to Phoenix to Joshua Tree National Park back to San Francisco. For Christmas I went to Latvia and then to UK.
I got back from Christmas travels on Sunday night the December 27th. I had 4 days left in the second quarter of my Personal PhD and I had weeks 9, 10, 11 of the course materials to finish.
So I spent 1.5 hours Monday morning before work, 2 hours after work, 1.5h Tuesday morning before work, 1h in the evening after work, again on Wed morning and evening. (I was getting up at 6am in the morning). Thursday I had off and it was the final push! Right before noon I finally submitted the final quiz! Then a screen appeared that said congratulations on finishing the course with 96.5% grade on quizzes and programming assignments. I am glad that the final weeks of the Coursera course didn’t have programming assignments. Those are more time consuming and I may not have finished in time.
So yeah, that’s what I get for procrastinating 🙂  but I am glad I still finished on time (by my own imposed deadline). After that I could celebrate New Years Eve with no remorse.
I hope I won’t procrastinate like this again. When getting back to it after a prolonged break there definitely was some time wasted to remember again the previous weeks materials as the material builds on each week.
Score: 1.0 out of 1.0.

Linguistics track

For my linguistics track for the second quarter I chose to read a book called Watching The English (the perks of setting my own curriculum 🙂 ). I have seen before when studying French that culture and language is intertwined, so I decided to read this book on culture and language of the English. It is a pretty long and dense book, but I really enjoyed it. Especially since the end of the year I spent few days in UK and was able confirm some observations.
Maybe someday I will write up about my takeaways from the book, but its not gonna be today to get this update out at somewhat reasonable time scale 🙂
Score: 1.0 out of 1.0.

Paper Reading

4. Read 10 more scientific papers on Speech Recognition.
 I didn’t really end up reading any new papers. However I am reading Ian Goodfellow’s draft book on Deep Learning and discussing it with my colleagues of how it relates to the work we do. I think each chapter of that book counts as a paper as each chapter is long and dives into existing research. I have read through 9 chapters with is 352 pages.
I am glad I did majority of the Coursera ML course before reading this book, it was a really good background for this reading.
Score: 0.9 out of 1.0


5. Write an update every other week.
Yeah, so I haven’t been doing well in this department. I wrote 5 updates in 12 weeks, which is the same as previous quarter. But doesn’t quite hit the target of writing every two weeks. I think this is the hardest part of it all.
Score: 0.83 out of 1.0


Overall score for the second quarter: 0.95 (compared to previous  quarter of 0.90) and I am happy that I managed to finish the Coursera course.

I will take some time to finalize the curriculum for the third quarter.

P.S. The formatting of this post is whacky, but I rather get it out imperfect than not do it at all.

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