Create a complex Machine Learning model in one line with Libra

栏目: IT技术 · 发布时间: 4年前

内容简介:So, what exactly is this Libra package? According to their statement, it is a machine learning API to let us build and deploy machine learning in just one line of code. How neat is that!Moreover, Target detection, preprocessing, and scoring are done by def

Libra

So, what exactly is this Libra package? According to their statement, it is a machine learning API to let us build and deploy machine learning in just one line of code. How neat is that!

Moreover, Target detection, preprocessing, and scoring are done by default. What we only need to do is selecting the model and input the data.

Let’s just try how it works.

Before we are installing our Libra package, we need to have Python 3.6 version or higher installed. Anything lower than that would not work. To install the package, we just need to run the following code in the command prompt.

pip install libra

After you have done installing the package, we would try how is the package works. Let’s set up all the necessary things we would use. First, for the purpose of our learning, I would use the dataset from Kaggle about education here . The following image is the data information.

Create a complex Machine Learning model in one line with Libra

Now, let’s say that we want to create a prediction model to classify the Class columns. Using Libra, it makes all things easier.

#The only thing we need to importfrom libra import client

In Libra, the dataset is still needed to be read from the external; say, CSV files. That is why we would create a client class that reads the file directly.

#Creating a client object that read the data to create the prediction modeledu_client = client('xAPI-Edu-Data.csv')

The above codes are all we need; The next part is more like querying the model in the way that we want and get the result immediately.

Currently, the only machine learning model present in Libra is:

  • Neural Network
  • Convolutional Neural Network
  • Support Vector Machine
  • Nearest Neighbors
  • Decision Tree
  • K-Means Clustering

And several Natural Language Processing , including:

  • Text Classification
  • Document Summarization
  • Image Caption Generation

Although, for our case, we only would try using the Neural Network model. Let’s try to create the prediction model then. In order to create a prediction model, we need to call the machine learning we want from the client method.

In our example, it would be .neural_network_query accepting a text in the parameter. The query we pass is a simple English text, such as ‘classify the class’ or ‘estimate accurately the StudentAbsenceDays’ . What is important is the target column; you need to specify it in the query. After that, the API would predict whether it is a classification or regression problem. Let’s see in the example below.

#Creating the model by simple query, for example classify the class. Using Libra, you would need to specify which column you want as the target and the rest would be preprocessed automaticallyedu_client.neural_network_query('classify the class')

Create a complex Machine Learning model in one line with Libra

Just using a simple query, the model is preprocessed automatically, and the learning process is initiated. Furthermore, all the repetition processes and the metrics also present immediately.

Create a complex Machine Learning model in one line with Libra

Additionally, the model presents us with the accuracy and model loss plot during each epoch.

If you want to know all the parameters you could pass in the model, please consult the API guide here .


以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网

查看所有标签

猜你喜欢:

本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们

具体数学

具体数学

Ronald L.Graham、Oren Patashnik、Donald E.Knuth / 张凡、张明尧 / 人民邮电出版社 / 2013-4-1 / 99.00元

本书介绍了计算机的数学基础,内容涉及求和、取整函数、数论、二项式系数、特殊数、母函数(发生函数)、离散概率、渐近等等,面向从事计算机科学、计算数学、计算技术诸方面工作的人员,以及高等院校相关专业的师生。一起来看看 《具体数学》 这本书的介绍吧!

HTML 压缩/解压工具
HTML 压缩/解压工具

在线压缩/解压 HTML 代码

HTML 编码/解码
HTML 编码/解码

HTML 编码/解码

正则表达式在线测试
正则表达式在线测试

正则表达式在线测试