295 lines
13 KiB
TypeScript
295 lines
13 KiB
TypeScript
import { load } from 'cheerio';
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import type { Route } from '@/types';
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import cache from '@/utils/cache';
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import ofetch from '@/utils/ofetch';
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import { parseDate } from '@/utils/parse-date';
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import { renderDescription } from './templates/description';
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export const handler = async (ctx) => {
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const { tag } = ctx.req.param();
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const limit = ctx.req.query('limit') ? Number.parseInt(ctx.req.query('limit'), 10) : 1;
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const rootUrl = 'https://www.deeplearning.ai';
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const currentUrl = new URL(`the-batch${tag ? `/tag/${tag.replace(/^tag\//, '').replace(/\/$/, '')}` : ''}/`, rootUrl).href;
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const response = await ofetch(currentUrl);
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const $ = load(response);
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const language = $('html').prop('lang');
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const data = JSON.parse($('script#__NEXT_DATA__').text());
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const nextBuildId = data.buildId;
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const posts = data.props?.pageProps?.posts ?? [];
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let items = posts.slice(0, limit).map((item) => {
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const title = item.title;
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const description = renderDescription({
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images: item.feature_image
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? [
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{
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src: item.feature_image,
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alt: item.feature_image_alt,
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},
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]
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: undefined,
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intro: item.excerpt ?? item.custom_excerpt,
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});
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const image = item.feature_image;
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const guid = `the-batch-${item.slug}`;
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return {
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title,
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description,
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pubDate: parseDate(item.published_at),
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link: new URL(`_next/data/${nextBuildId}/the-batch/${item.slug}.json`, rootUrl).href,
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category: item.tags.map((t) => t.name),
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guid,
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id: guid,
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content: {
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html: description,
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text: item.excerpt ?? item.custom_excerpt,
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},
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image,
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banner: image,
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language,
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};
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});
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items = await Promise.all(
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items.map((item) =>
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cache.tryGet(item.link, async () => {
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const detailResponse = await ofetch(item.link);
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const post = detailResponse.pageProps?.post ?? undefined;
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if (!post) {
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return item;
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}
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const $$ = load(post.html);
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$$('a').each((_, ele) => {
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if (ele.attribs.href?.includes('utm_campaign')) {
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const url = new URL(ele.attribs.href);
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url.searchParams.delete('utm_campaign');
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url.searchParams.delete('utm_source');
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url.searchParams.delete('utm_medium');
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url.searchParams.delete('_hsenc');
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ele.attribs.href = url.href;
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}
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});
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const title = post.title;
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const description = renderDescription({
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images: post.feature_image
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? [
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{
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src: post.feature_image,
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alt: post.feature_image_alt,
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},
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]
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: undefined,
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intro: post.excerpt ?? post.custom_excerpt,
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description: $$.html(),
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});
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const guid = `the-batch-${post.slug}`;
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const image = post.feature_image;
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item.title = title;
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item.description = description;
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item.pubDate = parseDate(post.published_at);
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item.link = new URL(`the-batch/${post.slug}`, rootUrl).href;
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item.category = post.tags.map((t) => t.name);
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item.author = post.authors.map((a) => a.name).join('/');
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item.guid = guid;
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item.id = guid;
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item.content = {
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html: description,
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text: post.excerpt ?? post.custom_excerpt,
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};
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item.image = image;
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item.banner = image;
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item.updated = parseDate(post.updated_at);
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item.language = language;
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return item;
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})
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)
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);
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const image = new URL($('meta[property="og:image"]').prop('content'), rootUrl).href;
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return {
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title: $('title').text(),
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description: $('meta[property="og:description"]').prop('content'),
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link: currentUrl,
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item: items,
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allowEmpty: true,
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image,
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author: $('meta[property="og:site_name"]').prop('content'),
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language,
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};
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};
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export const route: Route = {
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path: '/the-batch/:tag{.+}?',
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name: 'The Batch',
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url: 'www.deeplearning.ai',
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maintainers: ['nczitzk', 'juvenn', 'TonyRL'],
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handler,
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example: '/deeplearning/the-batch',
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parameters: { tag: 'Tag, Weekly Issues by default' },
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description: `::: tip
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If you subscribe to [Data Points](https://www.deeplearning.ai/the-batch/tag/data-points/)，where the URL is \`https://www.deeplearning.ai/the-batch/tag/data-points/\`, extract the part \`https://www.deeplearning.ai/the-batch/tag\` to the end, which is \`data-points\`, and use it as the parameter to fill in. Therefore, the route will be [\`/deeplearning/the-batch/data-points\`](https://rsshub.app/deeplearning/the-batch/data-points).
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:::
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| Tag | ID |
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| ---------------------------------------------------------------------- | -------------------------------------------------------------------- |
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| [Weekly Issues](https://www.deeplearning.ai/the-batch/) | [*null*](https://rsshub.app/deeplearning/the-batch) |
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| [Andrew's Letters](https://www.deeplearning.ai/the-batch/tag/letters/) | [letters](https://rsshub.app/deeplearning/the-batch/letters) |
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| [Data Points](https://www.deeplearning.ai/the-batch/tag/data-points/) | [data-points](https://rsshub.app/deeplearning/the-batch/data-points) |
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| [ML Research](https://www.deeplearning.ai/the-batch/tag/research/) | [research](https://rsshub.app/deeplearning/the-batch/research) |
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| [Business](https://www.deeplearning.ai/the-batch/tag/business/) | [business](https://rsshub.app/deeplearning/the-batch/business) |
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| [Science](https://www.deeplearning.ai/the-batch/tag/science/) | [science](https://rsshub.app/deeplearning/the-batch/science) |
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| [AI & Society](https://www.deeplearning.ai/the-batch/tag/ai-society/) | [ai-society](https://rsshub.app/deeplearning/the-batch/ai-society) |
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| [Culture](https://www.deeplearning.ai/the-batch/tag/culture/) | [culture](https://rsshub.app/deeplearning/the-batch/culture) |
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| [Hardware](https://www.deeplearning.ai/the-batch/tag/hardware/) | [hardware](https://rsshub.app/deeplearning/the-batch/hardware) |
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| [AI Careers](https://www.deeplearning.ai/the-batch/tag/ai-careers/) | [ai-careers](https://rsshub.app/deeplearning/the-batch/ai-careers) |
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#### [Letters from Andrew Ng](https://www.deeplearning.ai/the-batch/tag/letters/)
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| Tag | ID |
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| --------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- |
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| [All](https://www.deeplearning.ai/the-batch/tag/letters/) | [letters](https://rsshub.app/deeplearning/the-batch/letters) |
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| [Personal Insights](https://www.deeplearning.ai/the-batch/tag/personal-insights/) | [personal-insights](https://rsshub.app/deeplearning/the-batch/personal-insights) |
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| [Technical Insights](https://www.deeplearning.ai/the-batch/tag/technical-insights/) | [technical-insights](https://rsshub.app/deeplearning/the-batch/technical-insights) |
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| [Business Insights](https://www.deeplearning.ai/the-batch/tag/business-insights/) | [business-insights](https://rsshub.app/deeplearning/the-batch/business-insights) |
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| [Tech & Society](https://www.deeplearning.ai/the-batch/tag/tech-society/) | [tech-society](https://rsshub.app/deeplearning/the-batch/tech-society) |
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| [DeepLearning.AI News](https://www.deeplearning.ai/the-batch/tag/deeplearning-ai-news/) | [deeplearning-ai-news](https://rsshub.app/deeplearning/the-batch/deeplearning-ai-news) |
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| [AI Careers](https://www.deeplearning.ai/the-batch/tag/ai-careers/) | [ai-careers](https://rsshub.app/deeplearning/the-batch/ai-careers) |
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| [Just For Fun](https://www.deeplearning.ai/the-batch/tag/just-for-fun/) | [just-for-fun](https://rsshub.app/deeplearning/the-batch/just-for-fun) |
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| [Learning & Education](https://www.deeplearning.ai/the-batch/tag/learning-education/) | [learning-education](https://rsshub.app/deeplearning/the-batch/learning-education) |
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`,
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categories: ['programming'],
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features: {
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requireConfig: false,
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requirePuppeteer: false,
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antiCrawler: false,
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supportRadar: true,
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supportBT: false,
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supportPodcast: false,
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supportScihub: false,
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},
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radar: [
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{
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source: ['www.deeplearning.ai/the-batch', 'www.deeplearning.ai/the-batch/tag/:tag/'],
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target: (params) => {
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const tag = params.tag;
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return `/the-batch${tag ? `/${tag}` : ''}`;
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},
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},
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{
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title: 'Weekly Issues',
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source: ['www.deeplearning.ai/the-batch/'],
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target: '/the-batch',
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},
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{
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title: "Andrew's Letters",
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source: ['www.deeplearning.ai/the-batch/tag/letters/'],
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target: '/the-batch/letters',
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},
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{
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title: 'Data Points',
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source: ['www.deeplearning.ai/the-batch/tag/data-points/'],
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target: '/the-batch/data-points',
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},
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{
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title: 'ML Research',
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source: ['www.deeplearning.ai/the-batch/tag/research/'],
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target: '/the-batch/research',
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},
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{
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title: 'Business',
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source: ['www.deeplearning.ai/the-batch/tag/business/'],
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target: '/the-batch/business',
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},
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{
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title: 'Science',
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source: ['www.deeplearning.ai/the-batch/tag/science/'],
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target: '/the-batch/science',
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},
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{
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title: 'AI & Society',
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source: ['www.deeplearning.ai/the-batch/tag/ai-society/'],
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target: '/the-batch/ai-society',
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},
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{
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title: 'Culture',
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source: ['www.deeplearning.ai/the-batch/tag/culture/'],
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target: '/the-batch/culture',
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},
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{
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title: 'Hardware',
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source: ['www.deeplearning.ai/the-batch/tag/hardware/'],
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target: '/the-batch/hardware',
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},
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{
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title: 'AI Careers',
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source: ['www.deeplearning.ai/the-batch/tag/ai-careers/'],
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target: '/the-batch/ai-careers',
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},
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{
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title: 'Letters from Andrew Ng - All',
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source: ['www.deeplearning.ai/the-batch/tag/letters/'],
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target: '/the-batch/letters',
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},
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{
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title: 'Letters from Andrew Ng - Personal Insights',
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source: ['www.deeplearning.ai/the-batch/tag/personal-insights/'],
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target: '/the-batch/personal-insights',
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},
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{
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title: 'Letters from Andrew Ng - Technical Insights',
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source: ['www.deeplearning.ai/the-batch/tag/technical-insights/'],
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target: '/the-batch/technical-insights',
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},
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{
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title: 'Letters from Andrew Ng - Business Insights',
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source: ['www.deeplearning.ai/the-batch/tag/business-insights/'],
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target: '/the-batch/business-insights',
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},
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{
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title: 'Letters from Andrew Ng - Tech & Society',
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source: ['www.deeplearning.ai/the-batch/tag/tech-society/'],
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target: '/the-batch/tech-society',
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},
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{
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title: 'Letters from Andrew Ng - DeepLearning.AI News',
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source: ['www.deeplearning.ai/the-batch/tag/deeplearning-ai-news/'],
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target: '/the-batch/deeplearning-ai-news',
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},
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{
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title: 'Letters from Andrew Ng - AI Careers',
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source: ['www.deeplearning.ai/the-batch/tag/ai-careers/'],
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target: '/the-batch/ai-careers',
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},
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{
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title: 'Letters from Andrew Ng - Just For Fun',
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source: ['www.deeplearning.ai/the-batch/tag/just-for-fun/'],
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target: '/the-batch/just-for-fun',
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},
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{
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title: 'Letters from Andrew Ng - Learning & Education',
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source: ['www.deeplearning.ai/the-batch/tag/learning-education/'],
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target: '/the-batch/learning-education',
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},
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],
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};
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