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This is kind of a masters degree course i created for myself to get knowledge of Machine Learning from bottoms up First, you need a strong mathematical base. O
by neel8986 9y ago
This is kind of a masters degree course i created for myself to get knowledge of Machine Learning from bottoms up
First, you need a strong mathematical base. Otherwise, you can copy paste an algorithm or use an API but you will not get any idea of what is happening inside
Following concepts are very essential
1) Linear Algebra (MIT https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/ https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra... )
2) Probability (Harvard https://www.youtube.com/watch?v=KbB0FjPg0mw https://www.youtube.com/watch?v=KbB0FjPg0mw )
Get some basic grasp of machine learning. Get a good intuition of basic concepts
1) Andrew Ng coursera course (https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning)
2) Tom Mitchell book (https://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/0070428077 https://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/00...)
Both the above course and book are super easy to follow. You will get a good idea of basic concepts but they lack in depth. Now you should move to more intense books and courses
You can get more in-depth knowledge of Machine learning from following sources
1)Nando machine learning course ( https://www.youtube.com/watch?v=w2OtwL5T1ow https://www.youtube.com/watch?v=w2OtwL5T1ow)
2)Bishops book (https://www.amazon.in/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738 https://www.amazon.in/Pattern-Recognition-Learning-Informati...)
Especially Bishops book is really deep and covers almost all basic concepts.
Now for recent advances in Deep learning. I will suggest two brilliant courses from Stanford
1) Vision ( https://www.youtube.com/watch?v=NfnWJUyUJYU https://www.youtube.com/watch?v=NfnWJUyUJYU )
2) NLP ( https://www.youtube.com/watch?v=OQQ-W_63UgQ https://www.youtube.com/watch?v=OQQ-W_63UgQ)
The Vision course by Karparthy can be a very good introduction to Deep learning. Also, the mother book for deep learning ( http://www.deeplearningbook.org/ http://www.deeplearningbook.org/ )is good
- emurillo510 9y agohey neel8986, I know linear algebra is very important for large scale calculations. But how much calculus and statistics do you need for ML? Also, if you can touch what applications of calculus and statistics are used in ML that would be awesome :]. THANKS!
- neel8986 9y agoRegarding calculus, I think basic multivariable calculus can be enough for starting. If you need a refresher you can look for (https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/index.htm https://ocw.mit.edu/courses/mathematics/18-02sc-multivariabl...) Also the basic idea of chain rule is important for deep learning. Regarding statistics, I already mentioned the probability course which describes most of the important statistics concept you need. Also, some idea of Hypothesis testing can be helpful
- emurillo510 9y agoright on thanks neel8986.