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Simon Prince
2024-04-03 11:38:24 -04:00
commit d81bef8a6e
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130
src/components/Instructors/InstructorsElements.js Normal file
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import styled from "styled-components";
export const InstructorsContainer = styled.div`
color: #fff;
/* background: #f9f9f9; */
background: ${({lightBg}) => (lightBg ? '#57c6d1': '#010606')};
@media screen and (max-width: 768px) {
padding: 100px 0;
}
`
export const InstructorsWrapper = styled.div`
display: grid ;
z-index: 1;
width: 100% ;
max-width: 1100px;
margin-right: auto;
margin-left: auto;
padding: 0 24px;
justify-content: center;
`
export const InstructorsRow = styled.div`
display: grid;
grid-auto-columns: minmax(auto, 1fr);
align-items: center;
grid-template-areas: ${({imgStart}) => (imgStart ? `'col2 col1'` : `'col1 col2'`)};
@media screen and (max-width: 768px){
grid-template-areas: ${({imgStart}) => (imgStart ? `'col1' 'col2'` : `'col1 col1' 'col2 col2'`)};
}
`
export const InstructorsRow2 = styled.div`
display: grid;
grid-auto-columns: minmax(auto, 1fr);
align-items: top;
grid-template-areas: ${({imgStart}) => (imgStart ? `'col2 col1'` : `'col1 col2'`)};
@media screen and (max-width: 768px){
grid-template-areas: ${({imgStart}) => (imgStart ? `'col1' 'col2'` : `'col1 col1' 'col2 col2'`)};
}
`
export const Column1 = styled.div`
margin-bottom: 15px;
padding: 0 15px;
grid-area: col1;
`
export const Column2 = styled.div`
margin-bottom: 15px;
padding: 0 15px;
grid-area: col2;
`
export const TextWrapper = styled.div`
max-width: 540px ;
padding-top: 0;
padding-bottom: 0;
`
export const TopLine = styled.p`
color: #773c23;
font-size: 16px;
line-height: 16px;
font-weight: 700;
letter-spacing: 1.4px;
text-transform: uppercase;
margin-bottom: 16px;
`
export const Heading= styled.h1`
margin-bottom: 24px;
font-size: 48px;
line-height: 1.1;
font-weight: 600;
color: ${({lightText}) => (lightText ? '#f7f8fa' : '#010606')};
@media screen and (max-width: 480px)
{
font-size: 32px;
}
`
export const Subtitle = styled.p`
max-width: 440px;
margin-bottom: 35px;
font-size: 18px;
line-height: 24px;
color: ${({darkText})=> (darkText ? '#010606' : '#fff')};
`
export const BtnWrap = styled.div`
display: flex;
justify-content: flex-start;
`
export const ImgWrap = styled.div`
max-width: 555px;
height: 100%;
`
export const Img = styled.img`
width: 100%;
margin-top: 0;
margin-right: 0;
margin-left: 10px;
padding-right: 0;
`;
export const InstructorsContent = styled.div`
z-index: 3;
width: 100% ;
max-width: 1100px;
position: static;
padding: 8px 0px;
margin: 10px 0px;
display: flex;
flex-direction: column;
align-items: left ;
list-style-position: inside;
`

178
src/components/Instructors/index.js Normal file
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import React from 'react'
import { ImgWrap, Img, InstructorsContainer, InstructorsContent, InstructorsRow2, InstructorsWrapper, InstructorsRow, Column1, Column2, TextWrapper, TopLine, Heading, Subtitle} from './InstructorsElements'
// export const homeObjOne = {
// id: 'about',
// lightBg: false,
// lightText: true,
// lightTextDesc: true,
// topLine: 'Premium Bank',
// headline: 'Unlimited transactions with zero fees',
// description:
// 'Get access to our exclusive app that allows you to send unlimited transactions without getting charged any fees',
// buttonLabel: 'Get Started',
// imgStart: false,
// img: require('../../images/svg-1.svg').default,
// alt: 'Car',
// dark: true,
// primary: true,
// darkText: false
// };
import img from '../../images/instructor.svg'
const InstructorsSection = () => {
return (
<>
<InstructorsContainer lightBg={true} id='Instructors'>
<InstructorsWrapper>
<InstructorsRow imgStart={false}>
<Column1>
<TextWrapper>
<TopLine>Instructors</TopLine>
<Heading lightText={false}>Resources for instructors</Heading>
<Subtitle darkText={true}>All the figures in vector and image formats, full slides for first twelve chapters, instructor answer booklet</Subtitle>
</TextWrapper>
</Column1>
<Column2>
<ImgWrap>
<Img src={img} alt='Car'/>
</ImgWrap>
</Column2>
</InstructorsRow>
<InstructorsRow2>
<Column1>
<TopLine>Register</TopLine>
<a href="https://mitpress.ublish.com/request?cri=15055">Register</a> with MIT Press for answer booklet.
<InstructorsContent>
</InstructorsContent>
<TopLine>Full slides</TopLine>
<InstructorsContent>
Slides for 20 lecture undergraduate deep learning course:
</InstructorsContent>
<InstructorsContent>
<ol>
<li>Introduction <a href="https://drive.google.com/uc?export=download&id=17RHb11BrydOvxSFNbRIomE1QKLVI087m">PPTX</a></li>
<li>Supervised Learning <a href="https://drive.google.com/uc?export=download&id=1491zkHULC7gDfqlV6cqUxyVYXZ-de-Ub">PPTX</a></li>
<li>Shallow Neural Networks <a href="https://drive.google.com/uc?export=download&id=1XkP1c9EhOBowla1rT1nnsDGMf2rZvrt7">PPTX</a></li>
<li>Deep Neural Networks <a href="https://drive.google.com/uc?export=download&id=1e2ejfZbbfMKLBv0v-tvBWBdI8gO3SSS1">PPTX</a></li>
<li>Loss Functions <a href="https://drive.google.com/uc?export=download&id=1fxQ_a1Q3eFPZ4kPqKbak6_emJK-JfnRH">PPTX</a></li>
<li>Fitting Models <a href="https://drive.google.com/uc?export=download&id=17QQ5ZzXBtR_uCNCUU1gPRWWRUeZN9exW">PPTX</a></li>
<li>Computing Gradients <a href="https://drive.google.com/uc?export=download&id=1hC8JUCOaFWiw3KGn0rm7nW6mEq242QDK">PPTX</a></li>
<li>Initialization <a href="https://drive.google.com/uc?export=download&id=1tSjCeAVg0JCeBcPgDJDbi7Gg43Qkh9_d">PPTX</a></li>
<li>Performance <a href="https://drive.google.com/uc?export=download&id=1RVZW3KjEs0vNSGx3B2fdizddlr6I0wLl">PPTX</a></li>
<li>Regularization <a href="https://drive.google.com/uc?export=download&id=1LTicIKPRPbZRkkg6qOr1DSuOB72axood">PPTX</a></li>
<li>Convolutional Networks <a href="https://drive.google.com/uc?export=download&id=1bGVuwAwrofzZdfvj267elIzkYMIvYFj0">PPTX</a></li>
<li>Image Generation <a href="https://drive.google.com/uc?export=download&id=14w31QqWRDix1GdUE-na0_E0kGKBhtKzs">PPTX</a></li>
<li>Transformers and LLMs <a href="https://drive.google.com/uc?export=download&id=1af6bTTjAbhDYfrDhboW7Fuv52Gk9ygKr">PPTX</a></li>
</ol>
</InstructorsContent>
</Column1>
<Column2>
<TopLine>Figures</TopLine>
<InstructorsContent>
<ol>
<li> Introduction: <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap1PDF.zip">PDF</a> / <a href="https://drive.google.com/uc?export=download&id=1udnl5pUOAc8DcAQ7HQwyzP9pwL95ynnv"> SVG</a> / <a href="https://docs.google.com/presentation/d/1IjTqIUvWCJc71b5vEJYte-Dwujcp7rvG/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX </a></li>
<li> Supervised learning: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap2PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1VSxcU5y1qNFlmd3Lb3uOWyzILuOj1Dla"> SVG</a> / <a href="https://docs.google.com/presentation/d/1Br7R01ROtRWPlNhC_KOommeHAWMBpWtz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Shallow neural networks: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap3PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=19kZFWlXhzN82Zx02ByMmSZOO4T41fmqI"> SVG</a> / <a href="https://docs.google.com/presentation/d/1e9M3jB5I9qZ4dCBY90Q3Hwft_i068QVQ/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Deep neural networks: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap4PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1ojr0ebsOhzvS04ItAflX2cVmYqHQHZUa"> SVG</a>
/
<a href="https://docs.google.com/presentation/d/1LTSsmY4mMrJbqXVvoTOCkQwHrRKoYnJj/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Loss functions: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap5PDF.zip">PDF
</a> / <a href="https://drive.google.com/uc?export=download&id=17MJO7fiMpFZVqKeqXTbQ36AMpmR4GizZ">
SVG
</a> / <a
href="https://docs.google.com/presentation/d/1gcpC_3z9oRp87eMkoco-kdLD-MM54Puk/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Training models: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap6PDF.zip">PDF
</a> / <a href="https://drive.google.com/uc?export=download&id=1VPdhFRnCr9_idTrX0UdHKGAw2shUuwhK">
SVG
</a> / <a
href="https://docs.google.com/presentation/d/1AKoeggAFBl9yLC7X5tushAGzCCxmB7EY/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Gradients and initialization: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap7PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1TTl4gvrTvNbegnml4CoGoKOOd6O8-PGs"> SVG</a> / <a href="https://docs.google.com/presentation/d/11zhB6PI-Dp6Ogmr4IcI6fbvbqNqLyYcz/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Measuring performance: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap8PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=19eQOnygd_l0DzgtJxXuYnWa4z7QKJrJx"> SVG</a> / <a href="https://docs.google.com/presentation/d/1SHRmJscDLUuQrG7tmysnScb3ZUAqVMZo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Regularization: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap9PDF.zip">PDF
</a> / <a href="https://drive.google.com/uc?export=download&id=1LprgnUGL7xAM9-jlGZC9LhMPeefjY0r0">
SVG
</a> / <a
href="https://docs.google.com/presentation/d/1VwIfvjpdfTny6sEfu4ZETwCnw6m8Eg-5/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Convolutional networks: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap10PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1-Wb3VzaSvVeRzoUzJbI2JjZE0uwqupM9"> SVG</a> / <a href="https://docs.google.com/presentation/d/1MtfKBC4Y9hWwGqeP6DVwUNbi1j5ncQCg/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Residual networks: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap11PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1Mr58jzEVseUAfNYbGWCQyDtEDwvfHRi1"> SVG</a> / <a href="https://docs.google.com/presentation/d/1saY8Faz0KTKAAifUrbkQdLA2qkyEjOPI/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Transformers: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">PDF</a> / <a href="https://drive.google.com/uc?export=download&id=1txzOVNf8-jH4UfJ6SLnrtOfPd1Q3ebzd">
SVG</a> / <a
href="https://docs.google.com/presentation/d/1GVNvYWa0WJA6oKg89qZre-UZEhABfm0l/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Graph neural networks: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1lQIV6nRp6LVfaMgpGFhuwEXG-lTEaAwe"> SVG</a> / <a href="https://docs.google.com/presentation/d/1YwF3U82c1mQ74c1WqHVTzLZ0j7GgKaWP/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Unsupervised learning: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap14PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1aMbI6iCuUvOywqk5pBOmppJu1L1anqsM"> SVG</a> / <a href="https://docs.google.com/presentation/d/1A-lBGv3NHl4L32NvfFgy1EKeSwY-0UeB/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX</a></li>
<li> GANs: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap15PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1EErnlZCOlXc3HK7m83T2Jh_0NzIUHvtL"> SVG</a> / <a href="https://docs.google.com/presentation/d/10Ernk41ShOTf4IYkMD-l4dJfKATkXH4w/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Normalizing flows: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap16PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1B9bxtmdugwtg-b7Y4AdQKAIEVWxjx8l3"> SVG</a> / <a href="https://docs.google.com/presentation/d/1nLLzqb9pdfF_h6i1HUDSyp7kSMIkSUUA/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Variational autoencoders: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap17PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1SNtNIY7khlHQYMtaOH-FosSH3kWwL4b7"> SVG</a> / <a href="https://docs.google.com/presentation/d/1lQE4Bu7-LgvV2VlJOt_4dQT-kusYl7Vo/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Diffusion models: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap18PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1A-pIGl4PxjVMYOKAUG3aT4a8wD3G-q_r"> SVG</a> /
<a href="https://docs.google.com/presentation/d/1x_ufIBtVPzWUvRieKMkpw5SdRjXWwdfR/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX</a></li>
<li> Deep reinforcement learning: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap19PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1a5WUoF7jeSgwC_PVdckJi1Gny46fCqh0"> SVG</a> / <a href="https://docs.google.com/presentation/d/1TnYmVbFNhmMFetbjyfXGmkxp1EHauMqr/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX </a></li>
<li> Why does deep learning work?: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap20PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1M2d0DHEgddAQoIedKSDTTt7m1ZdmBLQ3"> SVG</a> / <a href="https://docs.google.com/presentation/d/1coxF4IsrCzDTLrNjRagHvqB_FBy10miA/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">
PPTX</a></li>
<li> Deep learning and ethics: <a
href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap21PDF.zip">PDF</a> / <a
href="https://drive.google.com/uc?export=download&id=1jixmFfwmZkW_UVYzcxmDcMsdFFtnZ0bU">SVG</a> / <a
href="https://docs.google.com/presentation/d/1EtfzanZYILvi9_-Idm28zD94I_6OrN9R/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
<li> Appendices - <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLAppendixPDF.zip">PDF</a> / <a href="https://drive.google.com/uc?export=download&id=1k2j7hMN40ISPSg9skFYWFL3oZT7r8v-l">
SVG</a> / <a
href="https://docs.google.com/presentation/d/1_2cJHRnsoQQHst0rwZssv-XH4o5SEHks/edit?usp=drive_link&ouid=110441678248547154185&rtpof=true&sd=true">PPTX</a></li>
</ol>
</InstructorsContent>
<a href="https://drive.google.com/file/d/1T_MXXVR4AfyMnlEFI-UVDh--FXI5deAp/view?usp=sharing">Instructions</a> for editing equations in figures.
<InstructorsContent>
</InstructorsContent>
</Column2>
</InstructorsRow2>
</InstructorsWrapper>
</InstructorsContainer>
</>
)
}
export default InstructorsSection