Add website

Author: Atcold

.gitmodules

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+[submodule "docs/jekyllbook"]
+	path = docs/jekyllbook
+	url = https://github.com/ebetica/jekyllbook

docs/404.html

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+jekyllbook/404.html

docs/_config.yml

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+permalink:           pretty
+
+# Setup
+title:               'Deep Learning'
+url:                 https://atcold.github.io/pytorch-Deep-Learning/
+baseurl:             '/pytorch-Deep-Learning'
+homepage_title:      Home
+default_lang:        'en'
+
+# About/contact
+author:
+name:                atcold
+url:                 https://twitter.com/alfcnz
+github:
+  repo:              https://github.com/atcold/pytorch-Deep-Learning/
+
+# Custom vars
+version:             dlsp20
+
+src:                 "."
+default_theme:       "ayu"
+
+defaults:
+  - scope:
+      path: "" # an empty string here means all files in the project
+    values:
+      layout: "custom"
+
+# For Maths
+markdown:            kramdown
+
+# To use hljs, disable the default highlighter
+kramdown:
+  syntax_highlighter_opts:
+    disable: true
+  math_engine: null
+
+exclude:
+  - jekyllbook
+  - en/index.md
+  - vendor
+
+################################### English ####################################
+# prologues:
+#   - path: en/about.md
+chapters:

docs/_layouts

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+jekyllbook/_layouts/

docs/index.md

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+---
+layout: default
+title: DEEP LEARNING
+author: Alfredo Canziani
+lang-ref: home
+---
+
+**DS-GA 1008 · SPRING 2021 · [NYU CENTER FOR DATA SCIENCE](http://cds.nyu.edu/)**
+
+| INSTRUCTORS | Yann LeCun & Alfredo Canziani |
+| LECTURES    | Wednesday 9:30 – 11:30, Zoom |
+| PRACTICA    | Tuesdays 9:30 – 10:30, Zoom |
+| FORUM       | [r/NYU_DeepLearning](https://www.reddit.com/r/NYU_DeepLearning/) |
+| MATERIAL    | [Notebooks 2020](https://github.com/Atcold/pytorch-Deep-Learning), [Notebooks 2021](https://github.com/Atcold/NYU-DLSP21) |
+
+
+## Description
+
+This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include: [DS-GA 1001 Intro to Data Science](https://cds.nyu.edu/academics/ms-curriculum/) or a graduate-level machine learning course.
+
+## Lectures
+
+Most of the lectures are similar to the previous edition, nevertheless, some are brand new.
+I will try to make clear the difference.

docs/jekyllbook

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+/usr/local/lib/ruby/gems/3.0.0/bin/jekyll serve --trace --baseurl '/NYU-DLSP21'

docs/serve.sh

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+jekyllbook/static/