这一轮对模型的学习已经完成。
在本系列中，可以学习如何用模型驱动开发方法来开发业务场景。
In this series, you'll learn how to use the Model Driven Development approach to develop a business scenario.
简单的连接点模型很适于粗粒度的方面，更容易学习。
Simple join point model is well suited to coarse-grained aspects and easier to learn.
为什么要学习一种新的绘图模型？
Ajax模型的每个成分都很容易学习。
评价是指将之前经过学习的模型应用到新数据上。
Scoring means to apply a previously learned model to new data.
如何使模型学习与记忆具有一定随机性。
How to make learning and memory of the model possess some randomness.
把这个思维模型牢牢的印在脑子里，接下来，学习什么是绑定目标。
With this model firmly in mind, let's learn about binding targets.
目前已提出了一些博弈学习模型，但都存在一定的局限性。
Some game learning models have been put forward but there are also some limitations.
学习策略的结构模型。
研究者为学习和记忆所创造出的一个基本模型就是计算机。
One basic model researchers have created for learning and memory is the computer.
没有我们能够学习的模型。
给出了该学习模型在组合数学问题求解中的应用。
The new Agent learning model can be applied in some problems of the combinatorics.
网格；远程教育；学习支持系统；移动代理；模型。
Grid; Distance Education; Learning Support System; Mobile Agent; Model.
首先，您将学习为您的模型创建汽车喷漆的过程。
First, you'll learn the process of car paint creation for your model.
针对文本中事件专题挖掘，提出事件模型学习算法。
For text-mining method of event topic, the method of event model was also proposed.
目的：建立合成语音的感知学习模型并验证该模型的学习效应。
AIM: to build a model of synthetic speech sound learning and to verify its effectiveness.
第二个趋势是用户模型的手动输入逐渐的被自动的机器学习所取代。
The other is that profile's manual input is being replaced by machine learning.
由于模型比较抽象，学习和使用不是很方便。
Since models are abstract, it is hard for us to learn and use.
该模型具有良好的适应性和自学习功能。
This model has good adaptability and self-learning function.
该模型具有以下特点：1机器自学习。
The features of this model are shown as follow: 1 Machine automatic learning.
用小鸡建立学习记忆模型研究学习记忆，具有成本低，周期短，实验重复性好等优点。
These model systems possess the advantages of low price, short period and easy to repeat.
就像机器学习算法自身一样，没有完美的模型，只有足够好的模型。
Like machine learning algorithms themselves, there is no perfect model, just a good enough model.
针对短行程控制(SSC)模型，开发了短行程控制在线自学习功能。
For the short stroke control (SSC) model, the SSC online self-learning function was exploited.
依据收集的大量实验室和现场测量数据，对该模型进行了学习和验证。
It is trained based on a large number of data atlaboratory and in field.
依据收集的大量实验室和现场测量数据，对该模型进行了学习和验证。
It is trained based on a large number of data atlaboratory and in field.
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