Learning Big Data Skills

"Csdn Live Report" December 2014 12-14th, sponsored by the China Computer Society (CCF), CCF large data expert committee contractor, the Chinese Academy of Sciences and CSDN jointly co-organized to promote large data research, application and industrial development as the main theme of the 2014 China Data Technology Conference (big Data Marvell Conference 2014,BDTC 2014) and the second session of the CCF Grand Symposium was opened at Crowne Plaza Hotel, New Yunnan, Beijing. 2014 China large data Technology ...

Since 2006, a topic called deep learning in the field of machine learning has begun to receive widespread attention in the academic world. Today it has become a boom in Internet big data and artificial intelligence.

Machine learning is almost ubiquitous, and even if we don't call them, they often appear in large data applications. I used to describe some typical big data use cases in my blog. In other words, these applications can provide the best results in "extreme situations". 　　At the end, I also mentioned the combination of byte-level data capacity, real-time data speed, and/or diversity of multiple structured data. I also listed a list of applications that deliberately avoided "machine learning analysis" during the collection process. The main reason is that while in these use cases machine learning is not primarily ...

Machine learning (Machine Learning) is a study of how computers simulate or implement human learning behavior in order to acquire new knowledge or skills, and to rearrange existing knowledge structures to continuously improve their performance. It is the core of artificial intelligence, is to make the computer has the basic way of intelligence, its application in all fields of artificial intelligence. Not long ago, the New York Times reported that Microsoft was applying machine learning to the business. Lightspeed, US investment director Jeremy Liew, also introduced "Big Data plus machine learning" to reshape bank credit ...

The Data Platform Business Unit first used not the MaxCompute (original ODPS) currently in use, but Hadoop. The original Hadoop cluster was named Cloud Ladder 1. At that time, Alibaba was also developing its own computing platform, which was the original ODPS, and named it. Cloud Ladder 2.

In the internet age, large data is hot, many people must pro data, but can really say that the big data is not much, not to mention how to use large data to dig out the great business value. 　　How do you define large data? What are the characteristics of large data? This paper aims to clarify the concept of large data, illustrate the application of large data and explore the future development of large data. 　　Q1: Is big Data a commercial hype? The industry's definition of large data is 4 "V": Large volume (Volume), multiple species (produced), fast (velocity) ...

At the heart of machine learning is "using algorithms to parse data, learn from it, and then make decisions or predictions about something in the world." This means that instead of explicitly writing a program to perform certain tasks, it is better to teach the computer how to develop an algorithm to accomplish the task.

The machine learning algorithm platform allows users to experiment by dragging visualized operational components so that engineers without a machine learning background can easily get started with data mining.

Intermediary transaction SEO diagnosis Taobao guest Cloud host technology Hall The first issue of last week's task is to ask students to bring a new microblog, 5 days to 500 listeners. This task is relatively simple, as long as the mastery of skills, only need 10 minutes a day to do, but also easy to complete the task. 　　The beginning of this week's 2nd phase is a lot harder than the first phase. One: 2 start task content: This week's task is to exercise the ability and efficiency of students to collect data, ask students to collect all the "Friendship link platform" type of website, ...

Today, I will share all the questions I encountered during the interview and share how to answer them. Some of these questions are relatively normal and have a certain theoretical background, but some are very innovative.