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My Top Reads in 2026
5
items My favorite books in 2026 so far. This list shows books from different genres I read and loved this year.
Sections
2
Fiction
Maths/Science
Fiction
Art is to the cultured what crime is to the commoner. Great pieces of art that moved me.
Gets you so attached with the characters, you are left with questions to ask them in real life. Full emotional rollercoaster, a beautiful slice of life and take on intrapersonal discoveries through the medium of such approachable characters.
Norwegian Wood | Barnes & Noble®
Every sentence from Lord Henry in this book can be made into a quote. It is a great reflection on morals, corruption, and conscience. It highlights the price one pays by devoting one's soul to beauty and sin.
The Picture of Dorian Gray by Oscar Wilde
My best short read yet. It captures the essence of family, responsibility, and life in a meaningful, emotion-packed bundle. Every character is so relatable, except for the misfortune that struck them. The emotions feel so real, and the book makes you...
The Metamorphosis
Maths/Science
I think we should all be a little more bayesian and less frequentist and that will solve all stereotypes and biases.
My favourite book for Deep Learning and AI covering various themes and techniques.
My top recommendation for developers who are versed in python and want start from zero and become intermediates in deep learning with practical details and hands-on examples.
I still keep coming back to this book whenever, I feel lost or confused about certain topics in deep learning.
My top recommendation for developers who are versed in python and want start from zero and become intermediates in deep learning with practical details and hands-on examples.
I still keep coming back to this book whenever, I feel lost or confused about certain topics in deep learning.
Deep Learning with Python, Third Edition
In depth guide to statistical concepts from very basics to intermediate level. Contains easy to follow examples and overall a fun read to enjoy everyday after work and build a theoretical base.
Head First Statistics: A Brain-Friendly Guide