So I'm finally at a point where I can say I'm done with my Machine Learning endeavour that I started about 19 months ago. Of course, learning is a lifelong process, but getting to the finish line of what seemed to be a far-fetched goal sometime back, feels incredibly sweet.
Some quick statistics:
- Number of courses completed: 6
- Number of courses partially completed: 3
- Number of programming assignments: 32
- Natural Language Processing: 3
- Machine Learning: 8
- Probabilistic Graphical models :9
- Neural Networks for Machine Learning: 4
- Computing for Data Analysis: 2
- Data Analysis: 2
- Design and Analysis of Algorithms: 4
- Number of Kaggle competitions entered: 4
- Notable rankings:
- 72/1158 in the Digit Recognition competition.
- 125/557 in the KDD Cup 2013-Author Paper Identification Challenge
- Ranked among the top 2% of all Kagglers.
This is the list of courses that I completed:
No
|
Course name
|
Completed
|
1
|
Probabilistic Graphical Models: Advanced track with distinction
|
June 2012
|
2
|
Dec 2012
|
|
3
|
Dec 2012
|
|
4
|
Dec 2012
|
|
5
|
Mar 2013 | |
6
|
Natural Language Processing with distinction
|
May 2013
|
Thoughts on getting here? In no particular order:
- Learning is incredibly fun. And self-motivated learning is much more fun than college. Motivation in college education is usually built around too much stick and too little carrot.
- Although online learning might seem very disconnected, the online student community is tight-knit and extremely helpful. I would not have completed certain assignments in PGM and NLP if not for other students who posted helpful tips.
- Support from family and friends matter a lot.
- Finishing a course is just one part of the story. Applying the learning in a real-world context is a very different challenge.
Blogs/books that I found helpful:
- Study Hacks, Cal Newport's blog
- Cal Newport: So good they can't ignore you
- Scott Young's blog
- The Kaggle blog
Other self-learners:
2 comments:
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