On May 5, 2018 with the feelings of expectation, watch the online technology Denver public class, the topic of the speaker’s AI, currently studying Al myself, do learn about image super-resolution and NLP, long night, the nuggets – give me a guidance technology community, light the way forward, this class I was feeling somewhat, Bosses have been zhihu was unknown, I sent in the first article of zhihu ever “why the development of the society more and more fast? – artificial intelligence could really make human eventually ruin site is as follows: https://zhuanlan.zhihu.com/p/36541542 welcome bosses.
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Nuggets please to two technology masters one is from seven Niuyun AI laboratory shao Jie Shao teacher, another is also from seven Niuyun AI laboratory Peng Yao Peng teacher.
Professor Shao mainly talked about the current research field of AI and the development and application of various aspects. For example, natural Language Processing, knowledge representation, automated reasoning.
Machine learning, Computer vision, robotics, and some learning suggestions for our friends who are new to AI, such as: (1) Don’t wait to master all the relevant mathematical knowledge before starting, because there are a lot of mathematical things, and it is very difficult, and energy is limited. You can make up for it when you need to use some mathematics.
(2) Do not collect too much learning materials, because the online information is complex, uneven quality, knowledge scattered, not systematic, precious time, limited energy.
(3) More hands-on, more practical operation, after all, computer is a relatively strong practical discipline. Next, Ms. Shao told us how to use learning algorithms to generate models from data, such as: Spam filters Search ranking Click through rate predict Recommendations Speech recognition Machine translation Face detection Image classification
At the same time to introduce algorithms to us is to need a case-by-case analysis, because the role of the algorithm is to need in a specific situation to play its maximum role, different algorithms apply to different systems. Teacher Shao also introduced the content of image processing, because it is very useful in daily life, such as video monitoring, image printing, medical image processing, satellite imaging, military reconnaissance and so on.
Machine learning: Using learning algorithms to generate models from data. To put it simply, it is based on written programs (machine algorithms) and a large amount of data to generate a model. In fact, deep learning neural network is commonly used now. The lecturer also talked about an example: for example, I often receive junk mail. When I receive it next time, I will analyze it according to the received junk mail and judge whether it is junk mail.
Machine learning: generalization (analyzing new data based on existing data), algorithm preference (matching different models, problems, applications to different algorithms).
As for machine learning, the K nearest neighbor method is also used to realize an image recognition. A solid knowledge of mathematics is required.
The teacher talked about the main contents of machine learning, including loss function, regular term, optimization, overparameter and so on. Recommended books are: Nick, A Brief History of Artificial Intelligence, Miroslav Kubat, Introduction to Machine Learning, Aurelien Geron, Hands-on Machine Learning with SciKit-Learn & Online courses recommended by Tensorflow, Ian Goodfellow, and Deep Learning (Flower Book) have a crash course in machine Learning Taiwan university professor Li Hongyi https://developers.google.com/machine-learning/crash-course/ http://speech.ee.ntu.edu.tw/~tlkagk/courses.html Wu En at http://mooc.study.163.com/smartSpec/detail/1001319001.htm cs231n http://cs231n.stanford.edu/ at Stanford university, Stanford university cs224n http://web.stanford.edu/class/cs224n/
Final question 1. Is it advisable to start with deep learning? 2. Phtroch and TensorFlow are two machine learning libraries. Which one is better to learn? 3. Practice is very important. How should we practice it? 4. What language is appropriate for AI development? 5. What are your suggestions for traditional software development industry (C language) and artificial intelligence industry (machine learning direction)? 6. What do you think of online machine learning courses such as Coursera? What are the optimization schemes from low resolution to high resolution in image processing? (This question was actually raised by me) At that time, the teacher replied that how did the low-resolution image come from, in fact, noise reduction or ordinary camera equipment can shoot it.
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Professor Peng Yao-Peng mainly talked about three aspects: 1. How does AI change our life? 2. The application of AI in Qiniuyun? Seven cloud cattle were introduced
7 Yunniu’s development achievements in the field of video and intelligence
And the core innovation system of qiyunniu’s ARTIFICIAL intelligence laboratory
Including (1) Content audit: using artificial intelligence machine vision technology, massive video image data to identify pornography, violence, terrorism and politics, to ensure the health of the Internet, radio and television, new media and government data dissemination content. (2) Eye of The City: It uses artificial intelligence machine vision technology to conduct rapid and efficient “detection, recognition and behavior analysis” of “people, objects and scenes”, so as to meet users’ scene requirements in “identity verification”, “intelligent security”, “large-scale image and video retrieval” and other aspects. Based on the core architecture of AI machine learning, the detection and recognition speed is fast. With the increase of sample size learning, the accuracy rate will improve rapidly. (3) Media asset intelligence (4) Broadcast control system (5) DORA intelligent multimedia API platform with an average of 10 billion yuan per day
3. Routine work of QIuniuyun AI engineer Types of engineers Computer vision algorithm engineer machine learning platform r&d engineer Big data platform r&d engineer search engine r&d engineer System architecture engineer Business architecture engineer
All right, that’s it. I feel like I got a lot! Thank you very much to the Nuggets and seven Clouds for this open lesson!!