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