Become A Machine Learning Engineer

This paper raises objections to this view, thinking that machine learning ≠ data statistics, deep learning has made a significant contribution to our handling of complex unstructured data problems, and artificial intelligence should be appreciated.

The scarcity of machine learning talent and the company's commitment to automating machine learning and completely eliminating the need for ML expertise are often on the headlines of the media.

The first is to learn from Facebook, but in the specific operations are very careful groping, so it is necessary to carry out in-depth discussion. 　　This article will be divided into a number of articles to introduce the content of the new barracks plan, the concept behind and operational attention to the details of the problem. What is a new barracks in fact, in February 2012, when Zuckerberg announced the IPO, he made it clear that "... Facebook requires all new recruits – including those who will not be primarily programming in the future – to join Boot camp (boot ...).

The writer Hangyuan, chief scientist of Huawei Noah's Ark laboratory. In this article I combined my personal experience, put forward to become a good engineer what needs? 　　We should follow the five principles: face the problem, solve the problem, solve the problem systematically, stand on the user's point of view, get the maximum benefit at the lowest cost; I have been in the research department of IT companies, and so far a total of three companies have worked: NEC, Microsoft, Huawei. The work content is different, both the base ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

Editor's note: Jay Kreps, a chief engineer from LinkedIn, says that logs exist almost at the time of the computer's creation, and there is a wide range of uses in addition to distributed computing or abstract distributed computing models. In this paper, he describes the principles of the log and the use of the log as a separate service to achieve data integration, real-time data processing and distributed system design. Article content is very dry, worth learning. Here's the original: I joined the LinkedIn company at an exciting time six years ago. From that time ...

[Large data 100 points] Presenter: Bai Moderator: Carey Organizer: Zhongguancun Large data Industry Alliance zhongguancun Large Data Industry alliance specially invited white teacher to take the first "Big Data 100" Forum keynote speaker! Bai is a chief engineer of Shanghai Stock Exchange, Ph. D., PhD. She is a ph. D. tutor at the Institute of Information Engineering, Chinese Academy of Sciences. Also serves as the executive director of Chinese Information Society of China, vice chairman of the Securities Sub-Committee of the National Financial Standardization Committee. White teacher research and work in the field across the academic, industrial ...

[Large data 100 points] Presenter: Bai Moderator: Carey Organizer: Zhongguancun Large data Industry Alliance zhongguancun Large Data Industry alliance specially invited white teacher to take the first "Big Data 100" Forum keynote speaker! Bai is a chief engineer of Shanghai Stock Exchange, Ph. D., PhD. She is a ph. D. tutor at the Institute of Information Engineering, Chinese Academy of Sciences. Also serves as the executive director of Chinese Information Society of China, vice chairman of the Securities Sub-Committee of the National Financial Standardization Committee. White teacher research and work in the field across the academic, industrial ...

Biopo (Eric Xing) is currently Professor of computer science at Carnegie Mellon University. His main research interests focus on the development of machine learning and statistical methodology and large-scale computing systems and architectures, in the hope of solving the problem of automated learning, reasoning, and decision making in a potential world of high dimensional, multiple peaks and dynamics in complex systems. Biopo has a Ph. D. In molecular biology from the University of Rochester and a PhD in computer science from the University of California, Berkeley. In December 2014 12-14th Beijing held the 2014 China Large Data Technology conference (Jinan second ...

Humans have never been satisfied with their cognitive abilities. Also because of this, photographic memory, Yimushihang, to know the geography of astronomy, has been seen as a model of human advanced version. The computer has already done this. Recently, at Alibaba's data opening days, I met with several data scientists. When they describe the future power of large data, I think of human limitations. The future of cognitive science is necessarily the perfect combination of computer and human. But what should this combination be? More and more data, and human interpretation of the ability is fixed, people will be tired, there will be no ...