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What to study? 본문
https://teachyourselfcs.com/#programming
전반적인 cs 지식 함양을 위해 배워야 할 것들 정리
Teach Yourself Computer Science
Frequently asked questions Who is the target audience for this guide? We have in mind that you are a self-taught software engineer, bootcamp grad or precocious high school student, or a college student looking to supplement your formal education with some
teachyourselfcs.com
we aim to provide the necessary mathematical skills to read those other books.
- Mathematical foundations
- Example machine learning algorithms that use the mathematical foundations
Mathematics for Machine Learning
Companion webpage to the book “Mathematics for Machine Learning”. Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press.
mml-book.github.io
make deep learning approachable, teaching you the the concepts, the context, and the code.
Dive into Deep Learning — Dive into Deep Learning 0.17.5 documentation
d2l.ai
http://cs231n.stanford.edu/schedule.html
Stanford University CS231n: Deep Learning for Computer Vision
04/20 Lecture 6: CNN Architectures Batch Normalization Transfer learning AlexNet, VGG, GoogLeNet, ResNet [slides] AlexNet, VGGNet, GoogLeNet, ResNet
cs231n.stanford.edu
https://github.com/ageron/handson-ml3
GitHub - ageron/handson-ml3: A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep L
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2. - GitHub - ageron/handson-ml3: A ser...
github.com
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