add quarto

Author: weijie-chen

linear-algebra-with-python/.gitignore

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linear-algebra-with-python/_book/index.html

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+[
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+    "href": "index.html",
+    "title": "Linear Algebra with Python",
+    "section": "",
+    "text": "0.1 Prerequisites\nThough the lectures are for beginners, it is beneficial that attendants had certain amount of exposure to linear algebra and calculus.\nAnd also the attendee are expected to have basic knowledge (3 days training would be enough) of - [x] Python - [x] NumPy - [x] Matplotlib - [x] SymPy\nAll the codes are written in an intuitive manner rather than efficient or professional coding style, therefore the codes are exceedingly straightforward, I presume barely anyone would have difficulty in understanding the codes.\nThe notes were written in JupyterLab, the interative plot requires ipympl. To install, type in conda install -c conda-forge ipympl if you have JupyterLab 3.x. Check ipymplpage for more details.",
+    "crumbs": [
+      "<span class='chapter-number'>1</span>  <span class='chapter-title'>Lectures of Linear Algebra</span>"
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+  },
+  {
+    "objectID": "index.html#environment-setup",
+    "href": "index.html#environment-setup",
+    "title": "Linear Algebra with Python",
+    "section": "0.2 Environment Setup",
+    "text": "0.2 Environment Setup\nI use poetry to management environment, if you happen to use VS code like me, please follow the steps below: 1. In Windows powershell and install poetry (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -p 2. Navigate to cd $env:APPDATA\\Python\\Scripts, check if poetry being installed. 3. Open a notepad notepad $profile and set alias for poetry Set-Alias poetry \"C:\\Users\\user\\AppData\\Roaming\\Python\\Scripts\\poetry.exe\" in notepad, I prefered this way, because sometimes setting env path not working in windows. 4. Reload profile by . $profile. 5. If you are on your personal computer Set-ExecutionPolicy RemoteSigned -Scope CurrentUser to unstrict your execution policy and choose Y. 6. Resume the default restricted policy for security Set-ExecutionPolicy Restricted -Scope CurrentUser. 7. Now check poetry --version, if you see the version printed, good to go. 8. You choose to use poetry update, or just manage version at your own convenience.",
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+      "<span class='chapter-number'>1</span>  <span class='chapter-title'>Lectures of Linear Algebra</span>"
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+    "objectID": "index.html#what-to-expect-from-notes",
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+    "title": "Linear Algebra with Python",
+    "section": "0.3 What to Expect from Notes",
+    "text": "0.3 What to Expect from Notes\nThese notes will equip you with most needed and basic knowledge for other subjects, such as Data Science, Econometrics, Mathematical Statistics, Financial Engineering, Control Theory and etc., which heavily rely on linear algebra. Please go through the tutorial patiently, you will certainly have a better grasp of the fundamental concepts of linear algebera. Then further step is to study the special matrices and their application with your domain knowledge.",
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+      "<span class='chapter-number'>1</span>  <span class='chapter-title'>Lectures of Linear Algebra</span>"
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+  {
+    "objectID": "index.html#contents",
+    "href": "index.html#contents",
+    "title": "Linear Algebra with Python",
+    "section": "0.4 Contents",
+    "text": "0.4 Contents\nChapter 1 - Linear Equation System Chapter 2 - Basic Matrix Algebra Chapter 3 - Determinant Chapter 4 - LU Factorization Chapter 5 - Vector Addition, Subtraction and Scalar Multiplication Chapter 6 - Linear Combination Chapter 7 - Linear Independence Chapter 8 - Vector Space and Subspace Chapter 9 - Basis and Dimension Chapter 10 -Null Space vs Col Space, Row Space and Rank Chapter 11 - Linear Transformation Chapter 12 - Eigenvalues and Eigenvectors Chapter 13b - Principal Component Analysis Chapter 13a - Diagonalization Chapter 14 - Applications to Dynamic System Chapter 15 - Innear Product and Orthogonality Chapter 16 - Gram-Schmidt Process and QR Decomposition Chapter 17 - Symmetric Matrices , Quadratic Form and Cholesky Decomposition Chapter 18 - The Singular Value Decomposition Chapter 19 - Multivariate Normal Distribution",
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+      "<span class='chapter-number'>1</span>  <span class='chapter-title'>Lectures of Linear Algebra</span>"
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+  {
+    "objectID": "index.html#screen-shots-examples",
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+    "title": "Linear Algebra with Python",
+    "section": "0.5 Screen Shots Examples",
+    "text": "0.5 Screen Shots Examples",
+    "crumbs": [
+      "<span class='chapter-number'>1</span>  <span class='chapter-title'>Lectures of Linear Algebra</span>"
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