machine learning是什么意思_machine learning的中文翻译

[计]机器学习（能力）；机器改进（能力）

learning machine───学习机；学习记录机；n.学习记录机

adversarial machine learning───对抗性机器学习

supervised machine learning───有监督的机器学习

learning───n.学习；学问；v.学习（learn的现在分词）

deploying a machine learning model───部署机器学习模型

machine───vt.用机器制造；n.机械，机器；机构；机械般工作的人；n.（Machine）（意）马基内（人名）

lifelong learning───终身学习；终生学习

learning tower───学习塔

e learning───n.网络（化）学习；数字（化）学习；电子（化）学习

Machine learning started making its way into industry in the early 90s.───机器学习在90年代早期开始进入工业领域。

Machine learning is now capable of far, far more complex tasks.───机器学习现在能够完成极其复杂的任务。

My company, Kaggle, operates on the cutting edge of machine learning.───我的公司 Kaggle 在机器学习领域处于领先地位。

Then we have research center in Grenoble, France where the focus is all on linguistics, machine learning.───我们在法国格勒诺布尔也有研究中心，研究重点是语言学和机器学习。

In machine learning, the data is often represented as a vector, sometimes called a feature vector.───在机器学习中，数据通常被表示为矢量，有时也称作特征矢量。

The algorithm of decision trees is well known due to simpleness and easy to realize in machine learning.───在各种机器学习算法中，决策树以其简单容易实现等特点被认可。

These abilities derive from something called machine learning, which is at the heart of many modern AI applications.───以上这些能力都源自一种叫机器学习的东西，它在许多现代人工智能应用中都处于核心地位。

At least one area of experience or knowledge in search, natural language processing, data mining, machine learning, distributed computing.───有搜索、自然语言处理、数据挖掘、机器学习、分布式计算等其中至少一个领域的经验或者知识；

Especially, the application of machine learning in Protein Structure Prediction is one of the hottest research areas in Bioinformatics.───特别的，蛋白质结构预测中的机器学习方法是其中研究的一个重要领域。

Their Android app uses machine learning and image recognition that takes place right on your phone to alert you when you're chatting your way right into an oncoming smash-up.

Support vector regression (SVR), a powerful machine learning technology based on statistical learning theory ( SLT ) was applied to QSAR on the aldose reductase inhibitory activity of 48 flavones.

Research Interests:statistical machine learning with applications to language, speech, image and biological signal processing.

And classification is the basis of the common Machine Learning problem.

As an effective machine learning method, ensemble learning has been widely used in various fields, such as corporation finance distress, exchange forecast and text mining.

To address second problem, we try some machine learning technologies on untagged corpus.

Machine learning optimization assessed value of the parameter words, and the ideas is the third innovative ideas of research projects.

Recently statistical machine learning methods have been substantially attempted for this issue with some achievements.

Her current research interests include biometrics, pattern recognition, machine learning and image processing.