Thứ Ba, 29 tháng 1, 2019

Notes for Math in Computer science

Gradient from KhanAcademy: "https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/gradient-and-directional-derivatives/v/why-the-gradient-is-the-direction-of-steepest-ascent"

Easy calculus by Thompsom 1941: "http://djm.cc/library/Calculus_Made_Easy_Thompson.pdf" or "http://www.gutenberg.org/ebooks/33283"

Coding matrix by Klein through Python Programming: "http://codingthematrix.com/" including vector, matrix, eigenvalue, Gaussian, SVD.

Matrix calculus for Deep learning: "https://explained.ai/matrix-calculus/index.html"

Learning Deep Learning from non-CS Ph.D.: "https://vimeo.com/214233053"

Free courses in DL: https://simoninithomas.github.io/Deep_reinforcement_learning_Course/

Practices in DL: https://www.fast.ai/2019/01/24/course-v3/

To become a data scientist, focus on coding: https://www.fast.ai/2017/03/23/focus-on-coding/

DL glossary: http://www.wildml.com/deep-learning-glossary/

TensorFlow is an open source C++/Python software library for numerical computation using data flow graphs, particularly Deep Neural Networks. It was created by Google. In terms of design, it is most similar to Theano, and lower-level than Caffe or Keras.

Open source for CS: https://github.com/mvillaloboz/open-source-cs-degree

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