diff --git a/src/components/Instructors/index.jsx b/src/components/Instructors/index.jsx
index 94b2388..e1bdf08 100644
--- a/src/components/Instructors/index.jsx
+++ b/src/components/Instructors/index.jsx
@@ -16,6 +16,240 @@ import {
TopLine,
} 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() {
return (
<>
@@ -34,7 +268,7 @@ export default function InstructorsSection() {
- 
+
@@ -52,84 +286,14 @@ export default function InstructorsSection() {
- -
- Introduction{" "}
-
- PPTX
-
-
- -
- Supervised Learning{" "}
-
- PPTX
-
-
- -
- Shallow Neural Networks{" "}
-
- PPTX
-
-
- -
- Deep Neural Networks{" "}
-
- PPTX
-
-
- -
- Loss Functions{" "}
-
- PPTX
-
-
- -
- Fitting Models{" "}
-
- PPTX
-
-
- -
- Computing Gradients{" "}
-
- PPTX
-
-
- -
- Initialization{" "}
-
- PPTX
-
-
- -
- Performance{" "}
-
- PPTX
-
-
- -
- Regularization{" "}
-
- PPTX
-
-
- -
- Convolutional Networks{" "}
-
- PPTX
-
-
- -
- Image Generation{" "}
-
- PPTX
-
-
- -
- Transformers and LLMs{" "}
-
- PPTX
-
-
+ {fullSlides.map((slide, index) => (
+ -
+ {slide.text}{" "}
+
+ PPTX
+
+
+ ))}
@@ -137,353 +301,23 @@ export default function InstructorsSection() {
Figures
- -
- {" "}
- Introduction:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX{" "}
-
-
-
- -
- {" "}
- Supervised learning:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Shallow neural networks:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Deep neural networks:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
-
- /
-
- PPTX
-
-
- -
- {" "}
- Loss functions:{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Training models:{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Gradients and initialization:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Measuring performance:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Regularization:{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Convolutional networks:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Residual networks:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Transformers:{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Graph neural networks:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Unsupervised learning:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- GANs:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Normalizing flows:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Variational autoencoders:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Diffusion models:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /
-
- PPTX
-
-
- -
- {" "}
- Deep reinforcement learning:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX{" "}
-
-
- -
- {" "}
- Why does deep learning work?:{" "}
-
- PDF
- {" "}
- /{" "}
-
- {" "}
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Deep learning and ethics:{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
- -
- {" "}
- Appendices -{" "}
-
- PDF
- {" "}
- /{" "}
-
- SVG
- {" "}
- /{" "}
-
- PPTX
-
-
+ {figures.map((figure, index) => (
+ -
+ {figure.text}:{" "}
+
+ PDF
+ {" "}
+ /{" "}
+
+ {" "}
+ SVG
+ {" "}
+ /{" "}
+
+ PPTX{" "}
+
+
+ ))}
diff --git a/src/components/NavBar/index.jsx b/src/components/NavBar/index.jsx
index 4654e59..7cc646c 100755
--- a/src/components/NavBar/index.jsx
+++ b/src/components/NavBar/index.jsx
@@ -53,7 +53,7 @@ export default function NavBar({ toggle }) {
smooth={true}
duration={500}
spy={true}
- exact="true"
+ exact={true}
offset={-80}
activeClass="active"
>
@@ -66,7 +66,7 @@ export default function NavBar({ toggle }) {
smooth={true}
duration={500}
spy={true}
- exact="true"
+ exact={true}
offset={-80}
activeClass="active"
>
@@ -79,7 +79,7 @@ export default function NavBar({ toggle }) {
smooth={true}
duration={500}
spy={true}
- exact="true"
+ exact={true}
offset={-80}
activeClass="active"
>
@@ -92,7 +92,7 @@ export default function NavBar({ toggle }) {
smooth={true}
duration={500}
spy={true}
- exact="true"
+ exact={true}
offset={-80}
activeClass="active"
>
diff --git a/src/components/Notebooks/index.jsx b/src/components/Notebooks/index.jsx
index de57e4d..40d847a 100644
--- a/src/components/Notebooks/index.jsx
+++ b/src/components/Notebooks/index.jsx
@@ -291,52 +291,54 @@ const notebooks = [
export default function NotebookSection() {
return (
-
-
-
-
-
- Coding exercises
-
- Python notebooks covering the whole text
-
-
- Sixty eight python notebook exercises with missing code to fill in
- based on the text
-
-
-
-
-
-
-
-
-
-
-
-
- {/* render first half of notebooks*/}
- {notebooks.slice(0, notebooks.length / 2).map((notebook, index) => (
- -
- {notebook.text}:{" "}
- ipynb/colab
-
- ))}
-
-
-
-
- {/* render second half of notebooks*/}
- {notebooks.slice(notebooks.length / 2).map((notebook, index) => (
- -
- {notebook.text}:{" "}
- ipynb/colab
-
- ))}
-
-
-
-
-
+ <>
+
+
+
+
+
+ Coding exercises
+
+ Python notebooks covering the whole text
+
+
+ Sixty eight python notebook exercises with missing code to fill
+ in based on the text
+
+
+
+
+
+
+
+
+
+
+
+
+ {/* render first half of notebooks*/}
+ {notebooks.slice(0, notebooks.length / 2).map((notebook, index) => (
+ -
+ {notebook.text}:{" "}
+ ipynb/colab
+
+ ))}
+
+
+
+
+ {/* render second half of notebooks*/}
+ {notebooks.slice(notebooks.length / 2).map((notebook, index) => (
+ -
+ {notebook.text}:{" "}
+ ipynb/colab
+
+ ))}
+
+
+
+
+
+
);
}