golang machine learning library

decision model can help the program provide support for financial analysis. Customer Segmentation: Identifies which users will be turned into the payment user for the product, and which will not, based on the behavior patterns of the user during the probation period and the behavior of all users in the past. Such a decision model can help the program with user intervention to persuade users to make early payments or better participate in product trials. Shape identification: Determi

its API is difficult to use. (Project address: Https://github.com/shogun-toolbox/shogun)2, KerasKeras is a high-level neural network API that provides a Python deep learning library. For any beginner, this is the best choice for machine learning because it provides a simpler way to express neural networks than other l

programming, and genetic algorithms. 8. The Datumbox machine learning Framework is an open source framework written in Java that allows rapid development of machine learning and statistical applications. The core focus of the framework is a large number of machine

. It provides a convenient mathematical tool by building numpy and matplotlib on the basis of existing python. The toolkit includes a number of simple and efficient tools that are ideal for data mining and data analysis.In the home page, you can see the user Guide, which is the entire machine learning index, where users can learn a variety of effective methods. In reference, users can find specific usage in

framework includes a large number of machine learning algorithms and statistical tests, which can process medium-scale datasets. 9. Deeplearning4j is the first commercial, open-source, and distributed Deep Learning Library written in Java and Scala. It is designed for commercial environments rather than as a research

it with input/output data. Because training a neural network consumes more resources, it is recommended to train the neural network in a node. JS environment rather than using a browser directly. On the official website, there is a small demo (PS: recognize color contrast) that can be used to identify colors, and this demo is now 404 pages.2. Deep PlaygroundThis is an entertaining web app that lets you explore different parts of the neural network in a game-based way. It has a friendly interfac

Java which allows the rapid development Mac Hine Learning and statistical applications. The main focus of the framework is to include a large number of machine learning algorithms statistical tests and be ing able to handle medium-large sized datasets. Deeplearning4j is the first Commercial-grade, Open-source, distributed deep-

computing tools. So we excluded Scipy (although we also use it !). Another thing that needs to be mentioned is that we will also evaluate these libraries based on the integration results with other scientific computing libraries, because Machine Learning (supervised or unsupervised) it is also part of the data processing system. If the database you use does not match other databases in the data processing

, linear algebra library to accelerate the calculation, the smaller batch, the acceleration effect may be less obvious. Of course, batch is not the bigger the better, too big, the weight of the update will be less frequent, resulting in the optimization process is too long. So mini-batch size, not static, according to your data set size, your device computing ability to choose. The the-Go is therefore-use some acceptable (but not necessarily-

Python Tools for machine learningPython is one of the best programming languages out there, with a extensive coverage in scientific Computing:computer VI Sion, artificial intelligence, mathematics, astronomy to name a few. Unsurprisingly, this holds true to machine learning as well.Of course, it has some disadvantages too; One of which is, the tools and libraries

contains nodes (mathematical operations) and edges (numerical arrays or tensor). 1.1 Datasets and modelsThe flexibility of TensorFlow is reflected in the possibility of research based on it or the repetition of machine learning tasks. Therefore, you can use a low-level API called TensorFlow Core. It allows you to control the model and train them using your own data set. But there are also public pre-traine

require the library to being written in Python; It was sufficient for it to have a Python interface. We also have a small sections on deep learning at the end as it has received a fair amount of attention recently. We don't aim to list all the machine learning libraries available in Python (the Python package inde

Liblinear instead of LIBSVM 2.Liblinear use, Java version Http://www.cnblogs.com/tec-vegetables/p/4046437.html 3.Liblinear use, official translation. http://blog.csdn.net/zouxy09/article/details/10947323/ http://blog.csdn.net/zouxy09/article/details/10947411 4. Here is an article, write good. Transferred from: http://blog.chinaunix.net/uid-20761674-id-4840097.html For the past more than 10 years, support vector machines (SVM machines) have been the most influential algorithms in

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job three q6-10 C + + implementation. Although there are many great gods in many blogs have given the implementation of Phython, but given the C + + implementation of the article is significantly less, here for everyone to prov

From http://www.infoq.com/cn/news/2014/07/pycon-2014This year's Pycon was held in Montreal, Canada on April 9, and Python has been widely used in academia thanks to its rapid prototyping capabilities. The recent official website has released videos and slideshows of the General Assembly tutorial section, including a number of (nearly half) content related to data mining and machine learning, as described in

Extensible System Framework (SSF) organizes these underlying compute, storage, and networking hardware technologies in a balanced Can accommodate supercomputers from small to large top 500, as well as a variety of compute-intensive and data-intensive scenarios.On top of that, Intel offers a highly optimized library of software and tools to maximize performance from the underlying hardware. The Intel Math Kernel L