独家｜关于深度学习，Yann LeCun给大学生的十四条建议

　　作者：Yann LeCun

　　本文长度为800字，建议阅读2分钟

　　本文是人工智能大师Yann LeCun在问答平台Quora上对问题“What’s your advice for undergraduate student who aspires to be a research scientist in deep learning or related field one day?”的回答。

　　［导读］Yann LeCun是深度学习研究领域内一个响当当的名字，卷积神经网络（Convolutional Neural Network）正是他的代表作。他为有志成为深度学习领域科研人员的大学生提出了14条建议，其中编号为0的是对于课程选择的建议，编号1-13则是完整的、可操作的成为科研人员的指导手册。

　　0. Take all the continuous math and physics class you can possibly take. If you have the choice between “iOS programming” and “quantum mechanics”, take “quantum mechanics”. In any case, take Calc I, Calc II, Calc III, Linear Algebra, Probability and Statistics, and as many physics courses as you can. But make sure you learn to program.

　　0. 尽可能持续参加所有数学和物理课程。如果你要在“iOS编程”和“量子力学”之间做出选择的话，那么选择“量子力学”。无论如何，都要选择微积分（一）、微积分（二）、微积分（三）、线性代数、概率与统计等课程，并且尽可能多的参加物理课程。但是要确保学会编程；

　　1. Take an AI-related problem you are passionate about.

　　1. 选择一个你热爱的、与人工智能有关的问题；

　　2. Think about it on your own.

　　2. 独立思考这个问题；

　　3. Once you have formed your own idea of it, start reading the literature on the problem.

　　3. 一旦你对这个问题形成了自己的想法，那么就开始阅读与学历提升有关的文献；

　　4. You will find that (a) your ideas were probably a bit naive but (b) your view of the problem is slightly different from what was done before.

　　4. 你会发现你的想法可能有点幼稚，但是你对待问题的看法已经和之前略有不同；

　　5. Find a professor in your school that can help you make your ideas concrete. It might be difficult. Professors are busy and don’t have much time for undergrads. The ones with the most free time are the very junior, the very senior, and the ones who are not very active in research.

　　5. 找你学校里的教授帮你把想法具体化。这可能会很难，因为教授都很忙，没有太多时间指导本科生。而有大量空闲时间的教授要么非常年轻，要么非常年迈，抑或是有些教授对研究工作并不十分积极；

　　6. If you don’ find a professor with spare time, hook up with a postdoc or PhD student in his/her lab.

　　6. 如果你找不到有空闲时间的教授，那么去实验室和那里的博士后或博士交流；

　　7. Ask the professor if you can attend his/her lab meetings and seminars or sit in his/her class.

　　7. 向教授询问你是否可以参加他/她的实验室会议和研讨会，或旁听他/她的课程；

　　8. Before you graduate, try to write a paper about your research or release a piece of open source code.

　　8. 在毕业之前，尝试写一篇与你的研究有关的论文或发布一段开源代码；

　　9. Now apply to PhD programs. Forget about the “ranking” of the school for now. Find a reputable professor who works on topics that you are interested in. Pick a person whose papers you like or admire.

　　9. 现在向博士项目提出申请。不要计较学校的“排名”，找一个在你感兴趣的课题领域进行研究工作且负有盛名的教授。你喜欢或欣赏谁的论文，你就选择那个人；

　　10. Apply to several PhD programs in the schools of the above-mentioned professors and mention in your letter that you’d like to work with that professor but would be open to work with others.

　　10. 向上述教授所任职学校的博士项目提出申请，并在信中提及你很想与那位教授共事，但也愿意考虑与其他教授合作；

　　11. Ask your undergrad professor to write a recommendation letter for you. It’s maximally efficient if your undergrad professor is known by your favorite PhD advisor.

　　11. 请求你的本科生导师为你写一封推荐信。如果你最喜欢的博士生导师认识你的本科生导师，那是最有效的；

　　12. If you don’t get accepted in one of your favorite PhD programs, get a job at Facebook or Google and try to get a gig as an engineer assisting research scientists at FAIR or Google Brain.

　　12. 如果你没能被任意一个你最喜欢的博士项目录取，那么就加入脸书或者谷歌，并尝试找一份工程师的临时工作，协助在FAIR或Google Brain工作的科研人员；

　　13. Publish a papers with the research scientists in question. Then re-apply to PhD programs and ask the FAIR or Google scientists you work with to write a recommendation letter for you.

　　13. 与上述的科研人员共同发表一篇论文。然后重新向博士项目提出申请，并请求在FAIR或Google Brain与你共事的科学家们为你写一封推荐信。