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instructors dynamic rendering

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Tom Heaton
2024-06-18 12:03:39 +01:00
parent f91e878eef
commit a96a14999f
3 changed files with 313 additions and 477 deletions
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src/components/Instructors/index.jsx
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@@ -16,6 +16,240 @@ import {
TopLine, TopLine,
} from "./InstructorsElements"; } from "./InstructorsElements";
const fullSlides = [
{
text: "Introduction",
link: "https://drive.google.com/uc?export=download&id=17RHb11BrydOvxSFNbRIomE1QKLVI087m",
},
{
text: "Supervised Learning",
link: "https://drive.google.com/uc?export=download&id=1491zkHULC7gDfqlV6cqUxyVYXZ-de-Ub",
},
{
text: "Shallow Neural Networks",
link: "https://drive.google.com/uc?export=download&id=1XkP1c9EhOBowla1rT1nnsDGMf2rZvrt7",
},
{
text: "Deep Neural Networks",
link: "https://drive.google.com/uc?export=download&id=1e2ejfZbbfMKLBv0v-tvBWBdI8gO3SSS1",
},
{
text: "Loss Functions",
link: "https://drive.google.com/uc?export=download&id=1fxQ_a1Q3eFPZ4kPqKbak6_emJK-JfnRH",
},
{
text: "Fitting Models",
link: "https://drive.google.com/uc?export=download&id=17QQ5ZzXBtR_uCNCUU1gPRWWRUeZN9exW",
},
{
text: "Computing Gradients",
link: "https://drive.google.com/uc?export=download&id=1hC8JUCOaFWiw3KGn0rm7nW6mEq242QDK",
},
{
text: "Initialization",
link: "https://drive.google.com/uc?export=download&id=1tSjCeAVg0JCeBcPgDJDbi7Gg43Qkh9_d",
},
{
text: "Performance",
link: "https://drive.google.com/uc?export=download&id=1RVZW3KjEs0vNSGx3B2fdizddlr6I0wLl",
},
{
text: "Regularization",
link: "https://drive.google.com/uc?export=download&id=1LTicIKPRPbZRkkg6qOr1DSuOB72axood",
},
{
text: "Convolutional Networks",
link: "https://drive.google.com/uc?export=download&id=1bGVuwAwrofzZdfvj267elIzkYMIvYFj0",
},
{
text: "Image Generation",
link: "https://drive.google.com/uc?export=download&id=14w31QqWRDix1GdUE-na0_E0kGKBhtKzs",
},
{
text: "Transformers and LLMs",
link: "https://drive.google.com/uc?export=download&id=1af6bTTjAbhDYfrDhboW7Fuv52Gk9ygKr",
},
];
const figures = [
{
text: "Introduction",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap1PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1udnl5pUOAc8DcAQ7HQwyzP9pwL95ynnv",
pptx: "https://docs.google.com/presentation/d/1IjTqIUvWCJc71b5vEJYte-Dwujcp7rvG/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Supervised learning",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap2PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1VSxcU5y1qNFlmd3Lb3uOWyzILuOj1Dla",
pptx: "https://docs.google.com/presentation/d/1Br7R01ROtRWPlNhC_KOommeHAWMBpWtz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Shallow neural networks",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap3PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=19kZFWlXhzN82Zx02ByMmSZOO4T41fmqI",
pptx: "https://docs.google.com/presentation/d/1e9M3jB5I9qZ4dCBY90Q3Hwft_i068QVQ/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Deep neural networks",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap4PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1ojr0ebsOhzvS04ItAflX2cVmYqHQHZUa",
pptx: "https://docs.google.com/presentation/d/1LTSsmY4mMrJbqXVvoTOCkQwHrRKoYnJj/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Loss functions",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap5PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=17MJO7fiMpFZVqKeqXTbQ36AMpmR4GizZ",
pptx: "https://docs.google.com/presentation/d/1gcpC_3z9oRp87eMkoco-kdLD-MM54Puk/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Training models",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap6PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1VPdhFRnCr9_idTrX0UdHKGAw2shUuwhK",
pptx: "https://docs.google.com/presentation/d/1AKoeggAFBl9yLC7X5tushAGzCCxmB7EY/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Gradients and initialization",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap7PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1TTl4gvrTvNbegnml4CoGoKOOd6O8-PGs",
pptx: "https://docs.google.com/presentation/d/11zhB6PI-Dp6Ogmr4IcI6fbvbqNqLyYcz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Measuring performance",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap8PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=19eQOnygd_l0DzgtJxXuYnWa4z7QKJrJx",
pptx: "https://docs.google.com/presentation/d/1SHRmJscDLUuQrG7tmysnScb3ZUAqVMZo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Regularization",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap9PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1LprgnUGL7xAM9-jlGZC9LhMPeefjY0r0",
pptx: "https://docs.google.com/presentation/d/1VwIfvjpdfTny6sEfu4ZETwCnw6m8Eg-5/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Convolutional networks",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap10PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1-Wb3VzaSvVeRzoUzJbI2JjZE0uwqupM9",
pptx: "https://docs.google.com/presentation/d/1MtfKBC4Y9hWwGqeP6DVwUNbi1j5ncQCg/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Residual networks",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap11PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1Mr58jzEVseUAfNYbGWCQyDtEDwvfHRi1",
pptx: "https://docs.google.com/presentation/d/1saY8Faz0KTKAAifUrbkQdLA2qkyEjOPI/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Transformers",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1txzOVNf8-jH4UfJ6SLnrtOfPd1Q3ebzd",
pptx: "https://docs.google.com/presentation/d/1GVNvYWa0WJA6oKg89qZre-UZEhABfm0l/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Graph neural networks",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1lQIV6nRp6LVfaMgpGFhuwEXG-lTEaAwe",
pptx: "https://docs.google.com/presentation/d/1YwF3U82c1mQ74c1WqHVTzLZ0j7GgKaWP/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Unsupervised learning",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap14PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1aMbI6iCuUvOywqk5pBOmppJu1L1anqsM",
pptx: "https://docs.google.com/presentation/d/1A-lBGv3NHl4L32NvfFgy1EKeSwY-0UeB/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "GANs",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap15PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1EErnlZCOlXc3HK7m83T2Jh_0NzIUHvtL",
pptx: "https://docs.google.com/presentation/d/10Ernk41ShOTf4IYkMD-l4dJfKATkXH4w/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Normalizing flows",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap16PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1SNtNIY7khlHQYMtaOH-FosSH3kWwL4b7",
pptx: "https://docs.google.com/presentation/d/1nLLzqb9pdfF_h6i1HUDSyp7kSMIkSUUA/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Variational autoencoders",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap17PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1B9bxtmdugwtg-b7Y4AdQKAIEVWxjx8l3",
pptx: "https://docs.google.com/presentation/d/1lQE4Bu7-LgvV2VlJOt_4dQT-kusYl7Vo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Diffusion models",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap18PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1A-pIGl4PxjVMYOKAUG3aT4a8wD3G-q_r",
pptx: "https://docs.google.com/presentation/d/1x_ufIBtVPzWUvRieKMkpw5SdRjXWwdfR/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Deep reinforcement learning",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap19PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1a5WUoF7jeSgwC_PVdckJi1Gny46fCqh0",
pptx: "https://docs.google.com/presentation/d/1TnYmVbFNhmMFetbjyfXGmkxp1EHauMqr/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Why does deep learning work?",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap20PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1M2d0DHEgddAQoIedKSDTTt7m1ZdmBLQ3",
pptx: "https://docs.google.com/presentation/d/1coxF4IsrCzDTLrNjRagHvqB_FBy10miA/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Deep learning and ethics",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap21PDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1jixmFfwmZkW_UVYzcxmDcMsdFFtnZ0bU",
pptx: "https://docs.google.com/presentation/d/1EtfzanZYILvi9_-Idm28zD94I_6OrN9R/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
{
text: "Appendices",
links: {
pdf: "https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLAppendixPDF.zip",
svg: "https://drive.google.com/uc?export=download&id=1k2j7hMN40ISPSg9skFYWFL3oZT7r8v-l",
pptx: "https://docs.google.com/presentation/d/1_2cJHRnsoQQHst0rwZssv-XH4o5SEHks/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true",
},
},
];
export default function InstructorsSection() { export default function InstructorsSection() {
return ( return (
<> <>
@@ -34,7 +268,7 @@ export default function InstructorsSection() {
</Column1> </Column1>
<Column2> <Column2>
<ImgWrap> <ImgWrap>
<Img src={img} alt="Car" /> <Img src={img} alt="Instructor" />
</ImgWrap> </ImgWrap>
</Column2> </Column2>
</InstructorsRow> </InstructorsRow>
@@ -52,84 +286,14 @@ export default function InstructorsSection() {
</InstructorsContent> </InstructorsContent>
<InstructorsContent> <InstructorsContent>
<ol> <ol>
<li> {fullSlides.map((slide, index) => (
Introduction{" "} <li key={index}>
<InstructorsLink href="https://drive.google.com/uc?export=download&id=17RHb11BrydOvxSFNbRIomE1QKLVI087m"> {slide.text}{" "}
PPTX <InstructorsLink href={slide.link}>
</InstructorsLink>
</li>
<li>
Supervised Learning{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1491zkHULC7gDfqlV6cqUxyVYXZ-de-Ub">
PPTX
</InstructorsLink>
</li>
<li>
Shallow Neural Networks{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1XkP1c9EhOBowla1rT1nnsDGMf2rZvrt7">
PPTX
</InstructorsLink>
</li>
<li>
Deep Neural Networks{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1e2ejfZbbfMKLBv0v-tvBWBdI8gO3SSS1">
PPTX
</InstructorsLink>
</li>
<li>
Loss Functions{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1fxQ_a1Q3eFPZ4kPqKbak6_emJK-JfnRH">
PPTX
</InstructorsLink>
</li>
<li>
Fitting Models{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=17QQ5ZzXBtR_uCNCUU1gPRWWRUeZN9exW">
PPTX
</InstructorsLink>
</li>
<li>
Computing Gradients{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1hC8JUCOaFWiw3KGn0rm7nW6mEq242QDK">
PPTX
</InstructorsLink>
</li>
<li>
Initialization{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1tSjCeAVg0JCeBcPgDJDbi7Gg43Qkh9_d">
PPTX
</InstructorsLink>
</li>
<li>
Performance{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1RVZW3KjEs0vNSGx3B2fdizddlr6I0wLl">
PPTX
</InstructorsLink>
</li>
<li>
Regularization{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1LTicIKPRPbZRkkg6qOr1DSuOB72axood">
PPTX
</InstructorsLink>
</li>
<li>
Convolutional Networks{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1bGVuwAwrofzZdfvj267elIzkYMIvYFj0">
PPTX
</InstructorsLink>
</li>
<li>
Image Generation{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=14w31QqWRDix1GdUE-na0_E0kGKBhtKzs">
PPTX
</InstructorsLink>
</li>
<li>
Transformers and LLMs{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1af6bTTjAbhDYfrDhboW7Fuv52Gk9ygKr">
PPTX PPTX
</InstructorsLink> </InstructorsLink>
</li> </li>
))}
</ol> </ol>
</InstructorsContent> </InstructorsContent>
</Column1> </Column1>
@@ -137,353 +301,23 @@ export default function InstructorsSection() {
<TopLine>Figures</TopLine> <TopLine>Figures</TopLine>
<InstructorsContent> <InstructorsContent>
<ol> <ol>
<li> {figures.map((figure, index) => (
{" "} <li key={index}>
Introduction:{" "} {figure.text}:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap1PDF.zip"> <InstructorsLink href={figure.links.pdf}>
PDF PDF
</InstructorsLink>{" "} </InstructorsLink>{" "}
/{" "} /{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1udnl5pUOAc8DcAQ7HQwyzP9pwL95ynnv"> <InstructorsLink href={figure.links.svg}>
{" "} {" "}
SVG SVG
</InstructorsLink>{" "} </InstructorsLink>{" "}
/{" "} /{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1IjTqIUvWCJc71b5vEJYte-Dwujcp7rvG/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true"> <InstructorsLink href={figure.links.pptx}>
PPTX{" "} PPTX{" "}
</InstructorsLink> </InstructorsLink>
</li> </li>
))}
<li>
{" "}
Supervised learning:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap2PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1VSxcU5y1qNFlmd3Lb3uOWyzILuOj1Dla">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1Br7R01ROtRWPlNhC_KOommeHAWMBpWtz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Shallow neural networks:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap3PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=19kZFWlXhzN82Zx02ByMmSZOO4T41fmqI">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1e9M3jB5I9qZ4dCBY90Q3Hwft_i068QVQ/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Deep neural networks:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap4PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1ojr0ebsOhzvS04ItAflX2cVmYqHQHZUa">
{" "}
SVG
</InstructorsLink>
/
<InstructorsLink href="https://docs.google.com/presentation/d/1LTSsmY4mMrJbqXVvoTOCkQwHrRKoYnJj/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Loss functions:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap5PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=17MJO7fiMpFZVqKeqXTbQ36AMpmR4GizZ">
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1gcpC_3z9oRp87eMkoco-kdLD-MM54Puk/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Training models:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap6PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1VPdhFRnCr9_idTrX0UdHKGAw2shUuwhK">
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1AKoeggAFBl9yLC7X5tushAGzCCxmB7EY/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Gradients and initialization:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap7PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1TTl4gvrTvNbegnml4CoGoKOOd6O8-PGs">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/11zhB6PI-Dp6Ogmr4IcI6fbvbqNqLyYcz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
</li>
<li>
{" "}
Measuring performance:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap8PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
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{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1SHRmJscDLUuQrG7tmysnScb3ZUAqVMZo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
Regularization:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap9PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1LprgnUGL7xAM9-jlGZC9LhMPeefjY0r0">
SVG
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PPTX
</InstructorsLink>
</li>
<li>
{" "}
Convolutional networks:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap10PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1-Wb3VzaSvVeRzoUzJbI2JjZE0uwqupM9">
{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1MtfKBC4Y9hWwGqeP6DVwUNbi1j5ncQCg/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
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<li>
{" "}
Residual networks:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap11PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1Mr58jzEVseUAfNYbGWCQyDtEDwvfHRi1">
{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1saY8Faz0KTKAAifUrbkQdLA2qkyEjOPI/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
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<li>
{" "}
Transformers:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1txzOVNf8-jH4UfJ6SLnrtOfPd1Q3ebzd">
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1GVNvYWa0WJA6oKg89qZre-UZEhABfm0l/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
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<li>
{" "}
Graph neural networks:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1lQIV6nRp6LVfaMgpGFhuwEXG-lTEaAwe">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1YwF3U82c1mQ74c1WqHVTzLZ0j7GgKaWP/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
</InstructorsLink>
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<li>
{" "}
Unsupervised learning:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap14PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1aMbI6iCuUvOywqk5pBOmppJu1L1anqsM">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1A-lBGv3NHl4L32NvfFgy1EKeSwY-0UeB/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
GANs:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap15PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1EErnlZCOlXc3HK7m83T2Jh_0NzIUHvtL">
{" "}
SVG
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/10Ernk41ShOTf4IYkMD-l4dJfKATkXH4w/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
Normalizing flows:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap16PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1SNtNIY7khlHQYMtaOH-FosSH3kWwL4b7">
{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1nLLzqb9pdfF_h6i1HUDSyp7kSMIkSUUA/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
Variational autoencoders:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap17PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1B9bxtmdugwtg-b7Y4AdQKAIEVWxjx8l3">
{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1lQE4Bu7-LgvV2VlJOt_4dQT-kusYl7Vo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
Diffusion models:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap18PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1A-pIGl4PxjVMYOKAUG3aT4a8wD3G-q_r">
{" "}
SVG
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PPTX
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<li>
{" "}
Deep reinforcement learning:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap19PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
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{" "}
SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1TnYmVbFNhmMFetbjyfXGmkxp1EHauMqr/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX{" "}
</InstructorsLink>
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<li>
{" "}
Why does deep learning work?:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap20PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
<InstructorsLink href="https://drive.google.com/uc?export=download&id=1M2d0DHEgddAQoIedKSDTTt7m1ZdmBLQ3">
{" "}
SVG
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/{" "}
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PPTX
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<li>
{" "}
Deep learning and ethics:{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap21PDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1EtfzanZYILvi9_-Idm28zD94I_6OrN9R/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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<li>
{" "}
Appendices -{" "}
<InstructorsLink href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLAppendixPDF.zip">
PDF
</InstructorsLink>{" "}
/{" "}
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SVG
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/{" "}
<InstructorsLink href="https://docs.google.com/presentation/d/1_2cJHRnsoQQHst0rwZssv-XH4o5SEHks/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX
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</li>
</ol> </ol>
</InstructorsContent> </InstructorsContent>
<InstructorsLink href="https://drive.google.com/file/d/1T_MXXVR4AfyMnlEFI-UVDh--FXI5deAp/view?usp=sharing"> <InstructorsLink href="https://drive.google.com/file/d/1T_MXXVR4AfyMnlEFI-UVDh--FXI5deAp/view?usp=sharing">

8
src/components/NavBar/index.jsx
View File

@@ -53,7 +53,7 @@ export default function NavBar({ toggle }) {
smooth={true} smooth={true}
duration={500} duration={500}
spy={true} spy={true}
exact="true" exact={true}
offset={-80} offset={-80}
activeClass="active" activeClass="active"
> >
@@ -66,7 +66,7 @@ export default function NavBar({ toggle }) {
smooth={true} smooth={true}
duration={500} duration={500}
spy={true} spy={true}
exact="true" exact={true}
offset={-80} offset={-80}
activeClass="active" activeClass="active"
> >
@@ -79,7 +79,7 @@ export default function NavBar({ toggle }) {
smooth={true} smooth={true}
duration={500} duration={500}
spy={true} spy={true}
exact="true" exact={true}
offset={-80} offset={-80}
activeClass="active" activeClass="active"
> >
@@ -92,7 +92,7 @@ export default function NavBar({ toggle }) {
smooth={true} smooth={true}
duration={500} duration={500}
spy={true} spy={true}
exact="true" exact={true}
offset={-80} offset={-80}
activeClass="active" activeClass="active"
> >

6
src/components/Notebooks/index.jsx
View File

@@ -291,6 +291,7 @@ const notebooks = [
export default function NotebookSection() { export default function NotebookSection() {
return ( return (
<>
<NotebookContainer lightBg={false} id="Notebooks"> <NotebookContainer lightBg={false} id="Notebooks">
<NotebookWrapper> <NotebookWrapper>
<NotebookRow imgStart={true}> <NotebookRow imgStart={true}>
@@ -301,8 +302,8 @@ export default function NotebookSection() {
Python notebooks covering the whole text Python notebooks covering the whole text
</Heading> </Heading>
<Subtitle darkText={false}> <Subtitle darkText={false}>
Sixty eight python notebook exercises with missing code to fill in Sixty eight python notebook exercises with missing code to fill
based on the text in based on the text
</Subtitle> </Subtitle>
</TextWrapper> </TextWrapper>
</Column1> </Column1>
@@ -338,5 +339,6 @@ export default function NotebookSection() {
</NotebookRow> </NotebookRow>
</NotebookWrapper> </NotebookWrapper>
</NotebookContainer> </NotebookContainer>
</>
); );
} }