Machine Learning Interview Questions:-
https://www.analyticsvidhya.com/blog/2018/06/comprehensive-data-science-machine-learning-interview-guide/
Understanding RNN and LSTM's:-
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
Understanding Attention:-
https://distill.pub/2016/augmented-rnns/
Reinforcement Learning:-
http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
BERT:-
https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/
http://jalammar.github.io/illustrated-bert/
https://jalammar.github.io/
Glue Datasets for Benchmarking:-
https://gluebenchmark.com/tasks/
http://snap.stanford.edu/data/web-Amazon.html
SVM's:-
https://blog.statsbot.co/support-vector-machines-tutorial-c1618e635e93
CNN Cheat Sheet:-
https://github.com/kanha95/books/blob/master/VIP%20Cheatsheet_%20Convolutional%20Neural%20Networks.pdf
Popular Blogs to Follow:-
https://brohrer.github.io/blog.html
Must Watch Short Videos:-
https://www.youtube.com/playlist?list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF
PROBABILITY:-
https://github.com/kanha95/books/blob/master/Probability%20Cheetsheet.pdf
The above link contains probability cheat sheet which would be helpful for gate and machine learning people. I will update this page as soon as i find good sources like this.
Book:- https://github.com/kanha95/books/blob/master/Ross_8th_ed_English.pdf
Challenging Problems:-
https://github.com/kanha95/books/blob/master/chpr.pdf
https://github.com/kanha95/books/blob/master/fifty_challenging_problems_in__2.pdf
https://github.com/kanha95/books/blob/master/241-Probability.pdf
https://github.com/kanha95/books/blob/master/stats_comp_07_08_q5_soln.pdf
https://www.analyticsvidhya.com/blog/2018/06/comprehensive-data-science-machine-learning-interview-guide/
Understanding RNN and LSTM's:-
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
Understanding Attention:-
https://distill.pub/2016/augmented-rnns/
Reinforcement Learning:-
http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
BERT:-
https://mccormickml.com/2019/05/14/BERT-word-embeddings-tutorial/
http://jalammar.github.io/illustrated-bert/
https://jalammar.github.io/
Glue Datasets for Benchmarking:-
https://gluebenchmark.com/tasks/
http://snap.stanford.edu/data/web-Amazon.html
SVM's:-
https://blog.statsbot.co/support-vector-machines-tutorial-c1618e635e93
CNN Cheat Sheet:-
https://github.com/kanha95/books/blob/master/VIP%20Cheatsheet_%20Convolutional%20Neural%20Networks.pdf
Popular Blogs to Follow:-
https://brohrer.github.io/blog.html
Must Watch Short Videos:-
https://www.youtube.com/playlist?list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF
PROBABILITY:-
https://github.com/kanha95/books/blob/master/Probability%20Cheetsheet.pdf
The above link contains probability cheat sheet which would be helpful for gate and machine learning people. I will update this page as soon as i find good sources like this.
Book:- https://github.com/kanha95/books/blob/master/Ross_8th_ed_English.pdf
Challenging Problems:-
https://github.com/kanha95/books/blob/master/chpr.pdf
https://github.com/kanha95/books/blob/master/fifty_challenging_problems_in__2.pdf
https://github.com/kanha95/books/blob/master/241-Probability.pdf
https://github.com/kanha95/books/blob/master/stats_comp_07_08_q5_soln.pdf
I appreciate your hard work, I will keep visiting it.
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Thank you sir for providing resources
ReplyDeleteSir one question how to choose courses at IIT Bombay if someone wants to make career in ml/ai
If someone not good at coding can I make career in ml/ai because there are only 14 months remaining for placement can I start now prepare for placement can I become software developer in 14 months or I have to stick only ml/ai
Please suggest
May I choose courses related to the ml/ai or or any one what other choosing
DeleteCourses are now in first semester
Foundation of ml
Design and engineering of computer science
Network security and cryptography
Algorithm and complexity
Software lab(compulsory)
Mathematics for visual computing
Program analysis
Dbms
New trend in it
Web mining
Advance architecture
First of al ml/ai is really a very vast area. And also don't use the term ml/ai because ml is totally different from ai. 3 months is enough for software development preparation even if you are bad at coding. People have done it. No doubt in those 3 months you have to dedicatedly solve many question from leetcode, hackerrank, interviewbit etc. You are new to IIT, so first complete all the compulsory courses. Then you would get a sense of efforts required and can decide wisely. In todays corporate world, you can switch between roles from software developer to ML engineer within a year by doing some courses online. You just need that IIT tag. In first sem don't choose many courses related to ml else seeing the maths and all you might get frustrated. Foundation of ml, algorithm and complexity and softwares lab seems reasonable. Don't worry too much. Just explore the things.
DeleteThank you so much sir you are doing a great work
DeleteThanks for sharing this informative links. If you want to Hire AI/ML Developers for your project. Please visit us.
ReplyDelete