In today's article, we will be discussing five machine learning interview questions. But before we do that just a quick disclaimer, these questions are not guaranteed to be asked at your interview. I pulled all today's questions and answers from our website, Mark questions dot com. Now let's get started.

在今天的文章中，我们将讨论五个机器学习面试问题。但在我们这样做之前，只是一个简短的免责声明，这些问题并不保证在你的面试中被问到。我从我们的网站上下载了今天所有的问题和答案。现在让我们开始吧。

Question number, one.
问题一。

In your opinion, what is the most valuable data applicable to our business? This is a general question which the interviewer will use to begin the conversation, learn more about your background and collect Information. They can use throughout the interview. This question seems that you've done some research on the company and industry and provide specific Information relevant to their business.

在您看来，适用于我们业务的最有价值数据是什么？这是一个一般性的问题，面试官将用它来开始谈话，了解更多关于你的背景和收集信息。他们可以在整个面试过程中使用。这个问题似乎你已经对公司和行业做了一些研究，并提供了与其业务相关的具体信息。

When preparing for an interview, you should find out as much as you can about the organization, the position you are interviewing four and interviewers background. This will help you anticipate the questions you will be asked and provide the Information you need to respond to them.

在准备面试时，你应该尽可能多地了解公司、你面试的职位以及面试官的背景。这将帮助你预测你将被问到的问题，并提供你需要回答这些问题的信息。

Since you are one of the leading organizations in the transportation industry, the most valuable data you can use to manage, your business involves the public use of transportation, the preferences, seasonal punctuations, and use of various modes of transportation. It would also be useful to know how transportation providers coordinate their activities to, create an efficient network.

由于您是运输行业的领先组织之一，您可以使用最有价值的数据来管理，您的业务涉及运输的公共使用、偏好、季节性标点和各种运输方式的使用。了解运输供应商如何协调其活动以创建高效网络也很有用。

Question number two, can you talk about deep learning? How compares to other machine learning algorithms? This is a general question related to the field of machine learning, but has some technical aspects. The interviewer uses it to better understand your communication style and your ability to discuss technical terms and simple, easy to understand language. The trick to these types of questions is not to over complicate them and spend too much time answering them.

第二个问题，你能谈谈深度学习吗？与其他机器学习算法相比如何？这是一个与机器学习领域相关的一般性问题，但有一些技术方面的问题。面试官用它来更好地了解你的沟通风格，以及你讨论技术术语和简单易懂的语言的能力。这类问题的诀窍是不要把它们搞得过于复杂，不要花太多时间来回答它们。

As with most interview questions being brief and to the point will serve as your best strategy. The interviewer will ask you a follow up question if they need additional Information. Deep learning is a subset of machine learning. It is focus on neural networks and how the leverage principles from neuroscience better model unlabeled and semi structure data. Algorithms employed in deep learning classified data through the use of neural networks.

与大多数面试问题一样，简明扼要将是你的最佳策略。如果面试官需要额外的信息，他们会问你一个后续问题。深度学习是机器学习的一个子集。它聚焦于神经网络以及来自神经科学的杠杆原理如何更好地建模未标记和半结构数据。深度学习中采用的算法通过使用神经网络对数据进行分类。

Question number three, do you have to go to algorithm? And can you describe to me? The purpose of this question is not to understand your favorite algorithm, but rather to see how you communicate. And if you're able to explain complex topics in simple language, during most interviews, you'll be speaking with someone familiar with the jobs technicalities for which you are interviewing.

第三个问题，你必须去算法吗？你能给我描述一下吗？这个问题的目的不是了解你最喜欢的算法，而是看你如何交流。如果你能用简单的语言解释复杂的话题，在大多数面试中，你将与熟悉你所面试的工作的技术细节的人交谈。

However, you may interview with someone from the personnel department or other business units within the company on some occasions, being able to explain complex concepts and simple, easy to understand language, demonstrates your ability to work cross functionally in the organization.

然而，在某些情况下，你可能会与人事部门或公司其他业务部门的人进行面试，能够解释复杂的概念和简单易懂的语言，证明你在组织中跨职能工作的能力。

My favorite type of algorithms involved, regression analysis, the process they use is to look at the way data performed in the past and use this to predict future trends. Along these, my favorite is decision for its regression. This type of algorithm is both accurate and requires little training time for the users.

我最喜欢的算法类型是回归分析，他们使用的过程是查看数据在过去的表现方式，并用它来预测未来的趋势。除了这些，我最喜欢的是它回归的决定。这种类型的算法既精确又需要用户很少的训练时间。

Question number four, what experience you have performing research in the field of machine learning? In addition to learning about your qualifications as a machine learning, engineer, organizations are interested in how you may have contributed to the technology. Candies who have done research, polish papers, conducted studies or otherwise enhance machine learning knowledge will have an advantage of those who simply perform work in this field.

第四个问题，你在机器学习领域有什么研究经验？除了了解你作为机器学习工程师的资格外，组织还对你如何为技术做出贡献感兴趣。做过研究、润色论文、进行过研究或以其他方式增强机器学习知识的人将比那些仅仅在该领域工作的人更有优势。

In several my previous positions, I work with senior machine learning experts on research projects related to artificial Intelligence. I was listed as an author of several publications about artificial Intelligence, augmented reality and other machine learning disciplines. Details of this are documented in my resume.

在我之前的几个职位上，我与高级机器学习专家一起从事与人工智能相关的研究项目。我被列为几本关于人工智能、增强现实和其他机器学习学科的出版物的作者。这方面的细节记录在我的简历中。

Question number five, what steps would you use to create and implement a database decision making system for our company's users? This is an operational question that the interviewer uses to better understand how you perform your job. The best way to respond to an operational question is the breakdown the processes you use into individual steps and briefly describe them in the order in which you execute them. Your answer to an operational question should be brief into the .. You should also anticipate follow up questions when creating a database decision making system.

第五个问题，你会用什么步骤来为我们公司的用户创建和实现一个数据库决策系统？这是一个操作性问题，面试官用它来更好地了解你的工作表现。回答操作问题的最佳方法是将您使用的流程分解为单独的步骤，并按照执行顺序简要描述它们。你对操作问题的回答应该简明扼要。在创建数据库决策系统时，您还应该预测后续问题。

The first thing I do is interview the users to understand the problems they are trying to solve. I then research the sources of Information that are relevant to the company's operations. Once I understand these, I create a system that incorporates databases, artificial Intelligence tools, and machine learning principles. The final step is to develop a user interface, which enables employees to quickly access Information they need.

我做的第一件事是采访用户，了解他们试图解决的问题。然后，我会研究与公司运营相关的信息来源。一旦我理解了这些，我就会创建一个包含数据库、人工智能工具和机器学习原理的系统。最后一步是开发一个用户界面，使员工能够快速访问他们需要的信息。感谢您的收看。