machine learning projects quora

Learning the learning notes series of OpenCV (2) source code compilation and sample projects, opencv learning notesDownload and install CMake3.0.1 To compile the source code of OpenCV2.4.9 by yourself, you must first download the compilation tool. CMake is the most widely used compilation tool. The following is an intr

understanding of the results of the model, so that we can make some adjustments to the model training. Can not blindly trust the results of model training. To sum up: In practical application, the hidden data is used more, the data processing should pay special attention to the cleaning of the exception, the proper sample sampling (over sampling or descending sampling) can adjust the positive and negative sample ratio, which is advantageous to the algorithm to train the real meaningful model; W

Great path to the gods-Great Integration of high-quality learning resources and projects for AndroidAndroid has many excellent learning resources, projects, and websites, but most of them are not concentrated, which is not conducive to beginners to learn and grasp Android as a whole. Today, we are just free to sort out

Machine learning is accelerating the pace of progress, it is time to explore this issue. Ai can really protect our systems in the future against cyber attacks. Today, an increasing number of cyber attackers are launching cyber attacks through automated technology, while the attacking enterprise or organization is still using manpower to summarize internal security findings, and then compare them with exter

applications, and currently only has the alpha version. One of the highlights of the Cloud machine Learning management platform, combined with TensorFlow, is the ability to support distributed computing for heterogeneous devices, which can run models automatically on every platform, from phones, single cpu/gpu to distributed systems with hundreds of GPU cards. Developers do not have to spend time o

Recommended BooksHere is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time series analysis from a Ba Yesian perspective. I

direction, technology selection and coding implementation (spark machine learning, depth learning technology). Product development including text categorization, emotional judgment, thematic clustering, events, and social relationships among people. (2) Modeling based on network security: Responsible for modeling direction, technology selection and coding implem

The author Matthew May is a computer postgraduate in parallel machine learning algorithms, and Matthew is also a data mining learner, a data enthusiast, and a dedicated machine-learning scientist. Open source tools play an increasingly important role in data science workflows. GitHub Ten deep

Turn: Http://www.infoq.com/cn/news/2014/04/learn-open-source Some suggestions for learning open source projectsAuthor Ben Linders released on April 11, 2014 | Note: GTLC Global Technology Leadership Summit, 500+CTO technical leadership redefined! 1 Discussions Share to: Weibo facebooktwitter Youdao Cloud Note email sharing Read later My list of reading With the development of open source communities and

In the introduction of recommendation system, we give the general framework of recommendation system. Obviously, the recommendation method is the most core and key part of the whole recommendation system, which determines the performance of the recommended system to a large extent. At present, the main recommended methods include: Based on content recommendation, collaborative filtering recommendation, recommendation based on association rules, based on utility recommendation, based on knowledge

-ported unix-like operating system that is the most current portable platform operating system and can be executed on many platforms, from 64bit Alpha servers to handheld devices and embedded devices. The slogan for the NetBSD program is: "Of course it runs NetBSD". Its simple design, code specification, and many advanced features make it highly acclaimed in the industry and academia. Due to its concise design and advanced features, it has excellent performance in both production and research, a

the file name of the data to iris.csv. The Code is as follows: 1 Is it easy? Just 12 lines of code is enough. Next, let's test it. According to the figure above, when we input 5 3.3 1.4 0.2, the output should be Iris-setosa. Let's take a look: Check that at least one original data is input and the correct result is obtained. But what if we enter data that is not in the original dataset? Let's test two groups: From the data of the two images we posted earlier, the data we input does not exist

a machine learning course at Stanford University. Take more course notes, complete course assignments as much as possible, and ask more questions. Read some books: This refers not to textbooks, but to the books listed above for beginners of programmers. Master a tool: Learn to use an analysis tool or class library, such as the python Machine