Subject Detail

Sno	Back	regulation	branch	year	semester	subject_code	name	credits	category
1	Back	R23AIML	ARTIFICIAL INTELLIGENCE & MACHINE LEARNING (AI&ML)	3	2	23A39601	ADVANCED MACHINE LEARNING	3.0	Theory

Syllabus List

Sno	subject	description	note	syllabus_file
1	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	23A39601	23A39601	Link

Book List

Sno	subject	title	author	publisher	edition	book_type	IMG	book_file	note
1	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	Deep Learning	Ian Goodfellow, Yoshua Bengio, and Aaron Courville	None	NOne	Textbook		Link	note
2	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	Machine Learning: A Probabilistic Perspective	Kevin P. Murphy	None	None	Textbook		Link	note
3	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	Pattern Recognition and Machine Learning	Christopher M. Bishop	Springer	None	Textbook		Link	note
4	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	Bayesian Reasoning and Machine Learning	David Barber	None	None	Reference		Link	note
5	ADVANCED MACHINE LEARNING - 23A39601 (Theory)	The Elements of Statistical Learning	Trevor Hastie, Robert Tibshirani, and Jerome Friedman	None	None	Reference		Link	note

OnlineReference List

Sno	subject	title	note

Question Paper List

Sno	Subject	Question Paper Type	Date	Title	File

Lab List

Sno	subject	date	title