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深度学习免费课程_2020年排名前三的免费深度学习课程

發(fā)布時(shí)間：2023/11/29 pytorch 118 豆豆

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深度學(xué)習(xí) 免費(fèi)課程

＃1 Fastai面向程序員的實(shí)用深度學(xué)習(xí)2020 (#1 Fastai Practical Deep Learning for Coders 2020)

On 21 of August 2020, fastai released the new version of the fastai library and of their Deep Learning course!

2020年8月21日，fastai發(fā)布了fastai庫(kù)及其深度學(xué)習(xí)課程的新版本！

Course page
課程頁(yè)面
YouTube Playlist
YouTube播放列表
Fastai forum
法泰論壇

This is my #1 recommendation for anyone wanting to start with practical Deep Learning. Fastai top-down teaching approach allows you to start applying your knowledge on real-world problems since day 1 and gradually dive into the details. Furthermore, you will learn to use the fastai library that is a very powerful tool to increase your productivity in all your Deep Learning projects!

對(duì)于任何想開(kāi)始實(shí)踐性深度學(xué)習(xí)的人， 這是我的第一建議 。從第一天開(kāi)始，Fastai自上而下的教學(xué)方法就可以開(kāi)始將您的知識(shí)應(yīng)用于實(shí)際問(wèn)題，并逐步深入研究細(xì)節(jié)。此外，您將學(xué)習(xí)使用fastai庫(kù)，它是一個(gè)非常強(qiáng)大的工具，可以提高所有深度學(xué)習(xí)項(xiàng)目的工作效率！

＃2 deeplearning.ai深度學(xué)習(xí)專業(yè) (#2 deeplearning.ai Deep Learning Specialization)

The deeplearning.ai online courses on Coursera are not free. However, all the course videos are freely available on YouTube!

Coursera上的deeplearning.ai在線課程不是免費(fèi)的。但是，所有課程視頻都可以在YouTube上免費(fèi)獲得 ！

Course 1: Neural Networks and Deep Learning
課程1： 神經(jīng)網(wǎng)絡(luò)與深度學(xué)習(xí)
Course 2: Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
課程2： 改善深度神經(jīng)網(wǎng)絡(luò)：超參數(shù)調(diào)整，正則化和優(yōu)化
Course 3: Structuring Machine Learning Projects
課程3： 構(gòu)建機(jī)器學(xué)習(xí)項(xiàng)目
Course 4: Convolutional Neural Networks
課程4： 卷積神經(jīng)網(wǎng)絡(luò)
Course 5: Sequence Models
課程5： 序列模型

Additionally, you can get further inspiration from these interviews with top Deep Learning researchers: Heroes of Deep Learning

此外，您可以從這些與深度學(xué)習(xí)頂尖研究人員的訪談中獲得更多啟發(fā)：深度學(xué)習(xí)英雄

These courses give you a good overview of Deep Learning, covering important topics with some depth but explained in a simple way by Andrew Ng. I would recommend watching these playlists after completing fastai course.

這些課程為您提供了深度學(xué)習(xí)的一個(gè)很好的概述，涵蓋了一些重要的主題，并且有深入的介紹，但由Andrew Ng進(jìn)行了簡(jiǎn)單說(shuō)明。我建議您在完成fastai課程后觀看這些播放列表。

＃3 MIT深度學(xué)習(xí)課程 (#3 MIT Deep Learning Courses)

MIT courses are another great resource! If you want to go even deeper into your Deep Learning studies online, consider the following playlists.

麻省理工學(xué)院的課程是另一個(gè)很棒的資源！如果您想進(jìn)一步深入研究在線深度學(xué)習(xí)，請(qǐng)考慮以下播放列表。

MIT 6.S191: Introduction to Deep Learning
MIT 6.S191：深度學(xué)習(xí)簡(jiǎn)介
Deep Learning State of the Art (2020)
深度學(xué)習(xí)最先進(jìn)的技術(shù)(2020)

If you watched the previous two courses these ones may give you complimentary information and additional perspective on some topics not covered before.

如果您觀看了前兩門課程，則這些課程可能會(huì)為您提供免費(fèi)的信息，并為您提供一些以前未涵蓋的主題的更多觀點(diǎn)。

接下來(lái)是什么？ (What next?)

Learning any skill requires practice and many hours of work. The free online resources available are more than enough for you to become a top deep learning practitioner. Sometimes the hardest part is to keep the motivation on. Watching the courses won’t make you an expert, putting your knowledge in practice will. For that Kaggle is probably the best place to be, where you can practice in real-world problems and share ideas with hundreds or thousands of other competitors. When you join your first Kaggle competition you will probably struggle to get a good result. Not giving up is what will make you learn the most, gain intuition and become an expert in the field.

學(xué)習(xí)任何技能都需要實(shí)踐和很多時(shí)間的工作。可用的免費(fèi)在線資源足以讓您成為頂尖的深度學(xué)習(xí)從業(yè)人員。有時(shí)最困難的部分是保持動(dòng)力。 觀看課程不會(huì)使您成為專家，而是將您的知識(shí)付諸實(shí)踐。 為此， Kaggle可能是最好的地方，您可以在其中練習(xí)實(shí)際問(wèn)題，并與成百上千的其他競(jìng)爭(zhēng)對(duì)手分享想法。當(dāng)您參加第一場(chǎng)Kaggle比賽時(shí)，您可能會(huì)很難取得好的成績(jī)。不放棄就是讓您學(xué)到最多，獲得直覺(jué)并成為該領(lǐng)域?qū)＜业脑颉?

總結(jié)和進(jìn)一步閱讀 (Final remarks and Further Reading)

If you find this story useful please consider joining my mailing list in this link so that you won’t miss any of my upcoming stories! You can read more about my Deep Learning journey on the following stories!

如果您覺(jué)得這個(gè)故事有用，請(qǐng)考慮通過(guò)此鏈接加入我的郵件列表 這樣您就不會(huì)錯(cuò)過(guò)任何我即將發(fā)表的故事！您可以在以下故事中閱讀有關(guān)我的深度學(xué)習(xí)之旅的更多信息！

Thanks for reading! Have a great day!

謝謝閱讀！祝你有美好的一天！

翻譯自: https://towardsdatascience.com/top-3-free-deep-learning-courses-in-2020-f2cd1c1b0f48