hugo.yaml

baseURL: https://example.org/
languageCode: en-us
title: MIT 18.065
theme: PaperMod

enableInlineShortcodes: true
enableRobotsTXT: true
buildDrafts: false
buildFuture: false
buildExpired: false
enableEmoji: true
pygmentsUseClasses: true

params:
  homeInfoParams:
    Title: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
    Content: Linear algebra concepts are key for understanding and creating machine learning algorithms, especially as applied to deep learning and neural networks. This course reviews linear algebra with applications to probability and statistics and optimization–and above all a full explanation of deep learning.

  socialIcons: # optional
    - name: "rss"
      url: "https://dafuzhuu.github.io/blog/"
    - name: "youtube"
      url: "https://ocw.mit.edu/courses/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/"
    - name: "cv"
      url: "https://math.mit.edu/~gs/learningfromdata/"
  ShowToc: true