经验 (Experience)

介绍 (Introduction)

LinkedIn has grown in popularity over the years, and it has become the social network space for professionals.

多年来，LinkedIn越来越流行，它已成为专业人士的社交网络空间。

I’ve seen many professionals utilize LinkedIn in various ways. Some use it as a personal brand-building tool, and others use it as a lead generation and marketing tool.

我已经看到许多专业人士以各种方式利用LinkedIn。 有些人将其用作个人品牌建立工具，而另一些人将其用作潜在客户生成和营销工具。

One prominent use of LinkedIn is to reach individuals for career and academic advice. These individuals might be out of reach physically, and therefore LinkedIn is a communication channel that bridges the physical distance between individuals.

LinkedIn的一种显着用途是吸引个人寻求职业和学术建议。 这些人的身体可能无法触及，因此，LinkedIn是沟通个人之间物理距离的沟通渠道。

Using LinkedIn as an advice platform is what this article focuses on. Individuals have read my articles, and have reached out to me via LinkedIn to get more information on specific topics and advice, all machine learning related.

本文重点介绍使用LinkedIn作为建议平台。 个人已经阅读了我的文章，并通过LinkedIn与我联系，以获取有关特定主题和建议(与所有机器学习相关的信息)的更多信息。

在本文中，我将包括机器学习从业人员和学生提出的一些常见问题，并且还将包括我提供的相应答案。 (In this article, I will include some common questions that have been asked by machine learning practitioners and students, and I’ll also include the corresponding answers I’ve provided.)

I have removed any names and personal information from questions to protect the identity of the individuals who have reached out to me.

我已删除问题中的所有姓名和个人信息，以保护与我联系的个人的身份。

如何阅读这篇文章 (How To Read This Article)

Questions asked by individuals will follow the format of this particular statement you are reading.

个人提出的问题将遵循您正在阅读的特定说明的格式 。

“Statements from me will look like this”

“我的陈述看起来像这样”

Answers will follow the format below:

答案将遵循以下格式：

回答： (Answer:)

A paragraph that includes a response to a question

包含对问题的回答的段落

问题1(在线学习) (Question 1 (Online Learning))

题： (Question:)

Hi Richmond, I am getting into Computer Vision and would appreciate if you had any course links/articles/ebooks that would help. Thanks!

里士满，您好，我正在学习计算机视觉，如果您有任何帮助的课程链接/文章/电子书，将不胜感激。 谢谢！

This is a common question that’s asked by curious individuals who want to gain some knowledge on the basics of machine learning related topics. I tend to direct new learners to free resources that I utilized. I believe it’s best to get a feel of subject areas and topics before putting monetary investments in purchasing courses and undertaking certificate programs.

这是一个常见的问题，好奇的人希望获得有关机器学习相关主题基础知识的知识。 我倾向于引导新学习者释放我所利用的资源。 我认为最好在将金钱投资用于购买课程和进行证书课程之前先了解主题领域和主题。

回答 (Answer)

To learn Computer Vision, you have to understand the basics of Machine Learning, Neural Networks and Image processing.

要学习计算机视觉，您必须了解机器学习，神经网络和图像处理的基础知识。

神经网络 (Neural Networks)

Within machine learning, it is essential to understand topics such as linear algebra, calculus, and partial differentiation.

在机器学习中，必须理解诸如线性代数，微积分和偏微分等主题。

Within Neural Networks, it is vital to understand the fundamental concepts and ideas. It is also important to understand concepts such as backpropagation, vanishing gradients descent and different neural network architectures such as convolutional neural networks (CNN); deep neural networks(DNN;) and recurrent neural networks(RNN).

在神经网络中，了解基本概念和想法至关重要。 了解诸如反向传播，消失梯度下降和不同的神经网络架构(例如卷积神经网络(CNN))等概念也很重要； 深度神经网络(DNN;)和递归神经网络(RNN)。

斯坦福大学计算机视觉讲座 (Stanford Computer Vision Lectures)

After understanding the basics of ML and Neural networks, you can dive into some academic content from Stanford that explains some standard Computer vision techniques, theory and algorithms.

了解ML和神经网络的基础知识之后，您可以深入斯坦福大学的一些学术内容，解释一些标准的计算机视觉技术，理论和算法。

深度蜥蜴机器学习和深度学习 (Deep Lizard Machine Learning & Deep Learning)

If you have a solid grasp of the theory and maths behind neural networks and some machine learning algorithms, you can move on to some practical projects and network implementations with a standard machine learning libraries such as PyTorch.

如果您对神经网络和某些机器学习算法背后的理论和数学有扎实的了解，则可以使用诸如PyTorch之类的标准机器学习库着手进行一些实际项目和网络实现。

With all the knowledge you have accumulated, you should be able to start your personal project and have the necessary expertise to get an entry-level computer vision job position.

借助您所积累的所有知识，您应该能够开始自己的项目并拥有必要的专业知识才能获得入门级的计算机视觉工作职位。

I will advise that you create your projects and participate in some Kaggle competition. Also, it would help if you tried to write on Medium to showcase your understanding of topics and concepts in computer vision and machine learning.

我建议您创建项目并参加一些Kaggle比赛。 另外，如果您尝试在Medium上写作，以展示您对计算机视觉和机器学习中的主题和概念的理解，也会有所帮助。

问题2(博士vs理学硕士) (Question 2 (PhD vs MSc))

题： (Question:)

I have recently started my first job as a grad in an AI role, specifically in Computer Vision. I have a bachelors degree in computer engineering but am considering starting the part-time Masters in AI at University, which I would do in my spare time outside work hours. Just wondering, have you ever considered a doing a PhD, or do you feel a master’s enough for working in the AI field?

我最近开始了我的第一份工作，担任AI职位的毕业生，尤其是Computer Vision。 我拥有计算机工程学士学位，但正在考虑在大学开设兼职的AI硕士学位，我会在工作时间以外的业余时间做这些工作。 只是想知道，您是否曾经考虑过要攻读博士学位，或者您觉得足以胜任AI领域的工作？

回答： (Answer:)

To answer your question directly, I think a Masters is more than enough for working in the AI field.

要直接回答您的问题，我认为硕士足以胜任AI领域的工作。

The benefit of an advanced qualification is that it provides academic authority and also shows to potential employers that you have taken the time out to specialize within a particular field.

高级资格证书的好处在于，它不仅可以提供学术权威，还可以向潜在的雇主表明您已经花了一些时间专门研究某个特定领域。

When conducting my job searches, I saw a few machine learning and AI roles that requested PhD degrees from an applicant, but most of these roles were either very specialized and within research departments of companies.

在进行求职时，我看到了一些需要申请人申请博士学位的机器学习和AI角色，但是其中大多数角色要么非常专业，要么在公司的研究部门内。

A PhD shows employers that you can dedicate time to one specific area of a field and become somewhat of an expert and make contributions to the advancement of the field. This is not entirely necessary for the majority of Machine learning roles in the industry.

博士学位向雇主表明，您可以将时间专用于某个领域的某个特定领域，并成为专家，可以为该领域的发展做出贡献。 对于行业中的大多数机器学习角色来说，这并不是完全必要的。

I would say you should go for the masters and give it your all and perhaps if you find an area within Machine learning that you are passionate about, then you can pursue a PhD.

我想说的是，您应该去找硕士学位，并全力以赴，也许如果您在机器学习中找到了自己热衷的领域，那么就可以攻读博士学位。

Currently, I am not considering a PhD as I want to build a solid five-year career track within Machine Learning and Computer Vision.

目前，我不考虑博士学位，因为我想在机器学习和计算机视觉领域建立扎实的五年职业生涯。

Perhaps I will evaluate my decision in 7 years or so.

也许我会在7年左右的时间内评估我的决定。

问题3(机器学习研究与工程) (Question 3 (Machine Learning Research vs Engineering))

题： (Question:)

I would wish to work in a position which is 50% researching on new, exciting stuff, reading, writing papers and 50% coding while also managing people, solving real-world problems(I understand that solving real-world problems is a part of research). I’m not sure if such a role exists. I feel I am at an important stage of my career where I need to take important life-shaping decisions. Considering your experience, it would be amazing if you could advise me on the above.

我希望工作的职位是50％的人研究新颖的东西，阅读，撰写论文和50％的编码，同时还要管理人员，解决现实问题(我知道解决现实问题是其中的一部分研究)。 我不确定是否存在这样的角色。 我觉得自己处于职业生涯的重要阶段，需要做出重要的人生决定。 考虑到您的经验，如果您能在上述方面给我建议，那将是惊人的。

回答： (Answer:)

In regards to finding a role that has a 50/50 balance between engineering and research, I’ll be honest with you and will tell you bluntly that not a lot of job roles can provide that balance or even define the right balance in the job role description.

关于找到在工程和研究之间保持50/50平衡的角色，我将对您诚实，直言不讳地告诉您，没有很多工作角色可以提供这种平衡，甚至无法在工作中定义正确的平衡角色描述。

As I mentioned in my article, there are a lot of engineers that conduct research and vice versa. But one crucial thing I didn’t mention is that the balance of ML researchers role and Engineering roles can be based on the current needs and requirement of the business.

正如我在文章中提到的，有很多工程师从事研究，反之亦然。 但是我没有提到的关键一件事是ML研究人员角色和工程角色之间的平衡可以基于业务的当前需求和要求。

I find the balance between engineering and researching changes during your time at a company and is based on the current goals and focus of the company.

我在公司任职期间发现工程变更和研究变更之间的平衡，并且该平衡基于公司当前的目标和重点。

Take me, for example, I applied for my current role, and in the job description and interview, it wasn’t stated that I would be conducting any in-depth research. But during the first two months, I did more research than engineering, but after the first two months till now, I do more engineering than research.

以我为例，我申请了目前的职位，在职位描述和面试中，并没有说我会进行任何深入的研究。 但是在最初的两个月中，我所做的研究比工程学要多，但是直到现在的头两个月，我所做的工程学比研究要多。

My advice is for you to carry on doing what you can to stand out from the crowd. Engineer tools that use state of the art machine learning approaches and also cultivate the skills of reading and writing research papers.

我的建议是让您继续做自己能从人群中脱颖而出的事情。 使用最先进的机器学习方法并培养阅读和撰写研究论文技能的工程师工具。

When you get to the stage where you are applying for roles, always ask for what the balance between engineering and research is.

当您进入申请职位的阶段时，请始终询问工程和研究之间的平衡是什么。

You’ll find that it is tough to get a role with the perfect 50/50 balance, but there are some job opportunities where you get to define the type of balance you want, although they are rare, they are still out there.

您会发现很难拥有完美的50/50平衡的角色，但是在一些工作机会中，您可以定义所需的平衡类型，尽管它们很少见，但仍然存在。

问题4(机器学习的职业可能性) (Question 4 (Machine Learning Career Possibility))

题： (Question:)

I always think about whether it’d be possible for me to become a computer vision engineer. I am not a PhD and don’t have a masters degree, I’m just a graduate. What would you suggest?

我一直在思考是否有可能成为一名计算机视觉工程师。 我不是博士学位，也没有硕士学位，我只是研究生。 你有什么建议？

回答 (Answer)

I would suggest looking at the requirement of job roles for Computer Vision Engineers where you are located.

我建议您查看您所在的计算机视觉工程师的职位要求。

Identify what skills, techniques, algorithms, programming languages and tools that you are expected to have an awareness of and ensure that you are on a path to acquiring them.

确定您期望了解哪些技能，技术，算法，编程语言和工具，并确保您正在逐步掌握它们。

Next, to make up for the lack of qualification, I would suggest looking into taking a masters degree if you can. But if you can’t pursue an advance degree in machine learning, then you can consider the following option:

接下来，为了弥补资格的不足，我建议您尽可能地考虑攻读硕士学位。 但是，如果您不能攻读机器学习的高级学位，那么可以考虑以下选择：

1. Taking online computer vision-related courses with a provided certificate upon completion. Udacity is suitable for this:

   完成时参加带有提供的证书的在线计算机视觉相关课程。 Udacity适合于此：

2. Have a project portfolio of 3–5 impressive computer vision/machine learning projects.

2.拥有3-5个令人印象深刻的计算机视觉/机器学习项目的项目组合。

3. Take a look at completing Kaggle challenges.

3.看一下完成Kaggle挑战的过程 。

结论 (Conclusion)

I hope that you have found some value from the content within this article.

我希望您从本文的内容中发现了一些价值。

It’s very humbling that there are people that view my experience and expertise as a learning point. If you have any questions that you would like to ask me, or perhaps you would prefer if I elaborated on answers to some question in more detail, then you can reach me through LinkedIn as usual.

有人将我的经验和专业知识视为学习要点，这是非常令人感到羞耻的。 如果您有任何疑问想问我，或者您更希望我详细说明某个问题的答案，那么您可以像往常一样通过LinkedIn与我联系。

I am not reluctant to answering machine learning related questions or queries as I know how hard and challenging the field can be, so please don’t be shy to ask any pressing questions. I’ll try my best to provide suitable answers.

我不愿意回答与机器学习相关的问题或疑问，因为我知道该领域可能有多么艰巨和挑战，所以请不要害羞地提出任何紧迫的问题。 我会尽力提供适当的答案。

我希望您觉得这篇文章有用。 (I hope you found the article useful.)

To connect with me or find more content similar to this article, do the following:

要与我联系或查找更多类似于本文的内容，请执行以下操作：

1. Subscribe to my Email List for weekly newsletters

   订阅我的电子邮件列表以获取每周新闻

2. Follow me on Medium

   跟我来中

3. Connect and reach me on LinkedIn

   在LinkedIn上联系并联系我