Apache Machine Learning Framework

C + + computer vision ccv-based on C language/provides cache/core machine Vision Library, novel Machine Vision Library opencv-It provides C + +, C, Python, Java and MATLAB interfaces, and supports Windows, Linux, Android and Mac OS operating system. General machine learning Mlpack dlib Ecogg Shark Closure Universal machine learning Closure Toolbox-cloj ...

Open source machine learning tools also allow you to migrate learning, which means you can solve machine learning problems by applying other aspects of knowledge.

The article is about machine learning, deep learning and AI: What is the difference? When it comes to new data processing techniques, we often hear many different terms. Some people say that they are using machine learning, while others call it artificial intelligence.

Machine learning engineers are part of the team that develops products and builds algorithms and ensures that they work reliably, quickly, and on a scale.

Computing is often used to analyze data, while understanding data relies on machine learning. 　　For many years, machine learning has been very remote and elusive to most developers. This is probably one of the most profitable and popular technologies now. 　　No doubt--as a developer, machine learning is a stage that can be a skill. Figure 1: Machine Learning composition machine learning is a reasonable extension of simple data retrieval and storage. 　　By developing a variety of components to make the computer more intelligent learning and behavior. Machine learning makes digging history count ...

Spam filtering, face recognition, recommendation engine-when you have a large dataset and want to use them to perform predictive analysis and pattern recognition, machine learning is the only way. In this science, computers can learn, analyze and manipulate data independently without prior planning, and more and more developers are now concerned with machine learning. The rise of machine learning technology is also important not only because hardware costs are getting cheaper and more powerful, but free software surges that machine learning is easily deployed on stand-alone or large-scale clusters The diversity of machine learning libraries means that whatever language you like ...

Cloudera, a Hadoop publisher, did not cause much concern when it bought a london-based start-up company last year Myrrix, and Cloudera rarely promoted the company's technology in machine learning. 　　But Myrrix's technology and his founder Sean Owen's value and influence in machine learning are not to be underestimated. 　　Owen is currently developing an open source machine learning Project--oryx (Oryx, Cloudera also sells a product called Impala, Impala). Oryx's goal is to help ...

Http://www.aliyun.com/zixun/aggregation/14417.html ">apache Hama 0.6.3 release, which is compatible with Hadoop 2, adds a BSP based machine learning algorithm, dynamic graphics API, etc. Hama is a computational framework based on BSP (Bulk Synchronous parallel Large-capacity synchronous parallel) computing technology, mainly for large-scale scientific computation.

How to use large data training risk control mathematical model has always been the challenge of PayPal in the detection of fraud transactions. PayPal has experienced four stages in the training of risk control model: Decision Tree: Early PayPal uses a simple decision tree model, mainly due to the small amount of data in the early model training, the result of the decision tree model is easy to explain. Logistic regression: When PayPal's business is becoming more and more complex, the split-control model is becoming more and more complex, and using logistic regression can easily handle larger data volumes and more features; and PayPal's line ...

& mathematic model of how to use big data to train risk control has always been PayPal's challenge in cheating transaction detection. PayPal's training in risk control models Roughly through four stages: Decision tree: early PayPal using a simple decision tree model, mainly due to the early model training data is relatively small, the decision tree model results easy ...