交易者必须学习概率，并放弃我们生活中学到的方方面面的技术技巧。
Traders, we find out, must learn to think in terms of probabilities and to surrender all of the skills we have acquired to achieve in virtually every other aspect of our lives.
目前，我正在学习你的概率课。
其实除了学习技术外，我们可以通过其他的方法来克服，大家知道，一个良好的环境，可以使人的思维更加敏捷，出错的概率就会减小！
Fact, apart from learning technology, we can by other means to overcome, you know, a good environment can give people thinking more agile, the probability of error will be reduced!
本文介绍和比较了概率参数学习的各种常用方法，并探求了它们在不同应用背景下的优缺点。
This paper introduces various common methods in probability data learning and make comparison among them under various application background.
提出了对随机事件概率分布参数进行自学习的方法，把知识化制造单元中的不确定因素纳入任务控制的数学模型。
The uncertain factors of the knowledgeable manufacturing cell were included in the task control model by utilizing a self-study method of probability distribution parameters of stochastic events.
对于已经学习了概率的交易者，没有两难的情况。
For the traders who have learned to think in probabilities, there is no dilemma.
统计与概率的学习第一次被放到了重要的位置上。
Have counted the study with probability and has been put to on the important position for the first time.
预备教师和在职数学教师都存在概率学习的错误认知。
At the last of this study, in order to enhance teacher's mathematics understanding of subject knowledge of probability.
学习本课程将使经济学家和其他社会科学研究人员获得扎实的概率与统计学基础知识。
This course will provide a solid foundation in probability and statistics for economists and other social scientists.
贝叶斯方法的特点是使用概率去表示所有形式的不确定性，学习或其他形式的推理都用概率规则来实现。
The characteristic of the Bayes method is to use probability to express the uncertainty of all forms, learning and the reasoning of other forms are all realized with the rule of probability.
本课程将为一年级学生进一步学习计量经济学提供必要的概率和统计背景。
The course provides the first-year graduate necessary probability and statistics background for the further study of econometrics.
利用概率模型训练、学习得到基于字形的汉越音译知识，实现汉语和越南语的人名音译。
A probabilistic model is used to get the transliteration information of Chinese-Vietnamese based on grapheme and the translation between Chinese and Vietnamese name is based on this information.
贝叶斯学习是一种基于已知的概率分布和观察到的数据进行推理，做出最优决策的概率手段。
Bayesian learning is a probability method that makes optimal decision based on known probability distribution and recently observed data.
而PAC学习模型是计算学习理论的基础，它为研究学习及泛化问题提供了一种基本的概率框架。
PAC learning model is the fundamental of computational learning theory, it provides a probabilistic framework for the study of learning and generalization.
另一方面，机器学习领域中概率图模型由于其灵活的建模方式和成熟的算法在很多领域取得不少成功。
On the other hand, probabilistic graphical models from the area of machine learning make several successes in various fields.
第四章主要是应用神经网络算法学习由数值计算得到的样本，实现了由夏比吸收能量值到断裂韧性值的在概率基础上的映射。
In the 4th chapter, the BP neural networks is used to study the sample data, thus realize the mapping from absorbing energy of Charpy Experiment to fracture toughness on the basis of probability.
贝叶斯学习理论使用概率去表示所有形式的不确定性，通过概率规则来实现学习和推理过程。
Bayesian learning Theory represents uncertainty with probability and learning and inference are realized by probabilistic rules.
此外还有一个人才管道的问题，女性和少数族裔学习STEM学科(指科学、技术、工程、数学，比如计算机科学)的概率要低于白人男性。
There's also a pipeline problem in which women and minorities do not study STEM subjects like computer science as frequently as white men.
比较而言，学习矢量量化网络在分类能力和训练成本方面更胜一筹，而概率神经网络则在计算负载和易用性方面更好一些。
By comparison, LVQ network was better than the others in classification ability and training cost, and PNN network in computation load and easy use.
这个专业学习统计学理论。课程包括概率理论，不同分析方法，使用设计，极限理论等。
Students in this major examine the theory behind statistics. Topics of instruction include probability theory, various methods of analysis, experimental design, limit theory, and more.
基于报价中标概率信念，本文建立了市场成员学习模型和决策模型。
Based on BABP, this thesis establishes the learning model and decision-making model of market participants.
概率论是表示不确定性的唯一合理的方法，概率论对于机器学习或不确定情况下的推理是有用的。
Probability theory is the only reasonable way to represent uncertainty, it is useful for machine learning or reasoning under uncertainty.
比较而言，学习矢量量化网络和概率神经网络在分类能力方面要比反向传播网络好一些，概率神经网络在计算负载方面比学习矢量量化网络要更胜一筹。
By comparison, LVQ network and PNN network are better than BPN network in classification ability, and PNN network is better than the others in computation load.
以概率乘法公式为理论依据，根据训练样本的PC A结果对PNN进行结构优化，并引入学习算法减小pnn的参数不确定性。
A probability multiplication formula was used as the theoretical foundation. The PNN structure was optimized based on statistical results from the PCA for the training samples.
本文讨论了在概率统计教学中开展创造教育，培养学生创造性思维的方法。这不仅提高了教学质量，而且还充分调动了学生学习的积极性和主动性。
The methods of developing students creative thinking and how to develop creative education in the teaching "Probability and Statistics" are discussed in the paper.
我们发现，职业的交易员必须学习用概率和可能性来思考，同时忘掉一切不相关的技巧-这些技巧很深的影响这我们，因为我们已经从它那里在别的方面得到好处。
Traders, we find out, must learn to think in terms of probabilities and to aurrender all of the skills we have acquired to achieve in virturally every other aspect of our lives.
对典型的竞争学习算法进行了研究和分析，提出了一种基于神经元获胜概率的概率敏感竞争学习算法（PSCL）。
Neural network competitive learning algorithms are widely used for vector quantization. In this paper, some typical competitive learning algorithms have been specially investigated and analyzed .
但是小孩子有过两次全麻手术，风险概率（在学习能力上不如其他孩子）是1.5倍。
But kids who had had two surgeries were one and a half times more at risk.
但是小孩子有过两次全麻手术，风险概率（在学习能力上不如其他孩子）是1.5倍。
But kids who had had two surgeries were one and a half times more at risk.
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