拍照背墙效果图:谁有关于机器学习或JAVA的英文啊还有翻译

机器学习(Machine Learning)是研究计算机怎样模拟或实现人类的学习行为，以获取新的知识或技能，重新组织已有的知识结构使之不断改善自身的性能。它是人工智能的核心，是使计算机具有智能的根本途径，其应用遍及人工智能的各个领域，它主要使用归纳、综合而不是演译。

学习能力是智能行为的一个非常重要的特征，但至今对学习的机理尚不清楚。人们曾对机器学习给出各种定义。H.A.Simon认为，学习是系统所作的适应性变化，使得系统在下一次完成同样或类似的任务时更为有效。R.s.Michalski认为，学习是构造或修改对于所经历事物的表示。从事专家系统研制的人们则认为学习是知识的获取。这些观点各有侧重，第一种观点强调学习的外部行为效果，第二种则强调学习的内部过程，而第三种主要是从知识工程的实用性角度出发的。

机器学习在人工智能的研究中具有十分重要的地位。一个不具有学习能力的智能系统难以称得上是一个真正的智能系统，但是以往的智能系统都普遍缺少学习的能力。例如，它们遇到错误时不能自我校正；不会通过经验改善自身的性能；不会自动获取和发现所需要的知识。它们的推理仅限于演绎而缺少归纳，因此至多只能够证明已存在事实、定理，而不能发现新的定理、定律和规则等。随着人工智能的深入发展，这些局限性表现得愈加突出。正是在这种情形下，机器学习逐渐成为人工智能研究的核心之一。它的应用已遍及人工智能的各个分支，如专家系统、自动推理、自然语言理解、模式识别、计算机视觉、智能机器人等领域。其中尤其典型的是专家系统中的知识获取瓶颈问题，人们一直在努力试图采用机器学习的方法加以克服。

机器学习的研究是根据生理学、认知科学等对人类学习机理的了解，建立人类学习过程的计算模型或认识模型，发展各种学习理论和学习方法，研究通用的学习算法并进行理论上的分析，建立面向任务的具有特定应用的学习系统。这些研究目标相互影响相互促进。
Machine learning (Machine Learning) is to study how computer simulation or the realization of human learning, to acquire new knowledge or skills, the knowledge structure has been reorganized to continually improve their own performance. It is the core of artificial intelligence, wisdom is a fundamental way to the computer, its applications across all areas of artificial intelligence, summarized its main use, but not when it comes to interpretation of the integrated. Learning ability is a very important wisdom acts features, but so far it is not clear mechanisms for learning. People have given various definitions machine learning. H.A.Simon believe that learning is the adaptive system changes that the next system to complete the same or similar tasks more effectively. R.s.Michalski believe that learning is constructed or modified to experience things said. It is engaged in the development of expert systems that learning is the acquisition of knowledge. These views have different emphases, and the first point of the study emphasized external effects, and the second is that the internal learning process, and a third mainly works from the knowledge of the utility perspective. Machine learning in artificial intelligence research a very important position. Does not have a system to be able to learn wisdom is a true intelligent system, but the system is a general lack of wisdom and ability. For example, they can not be self - encounter error correction; Will not improve their performance through experience; Not automatically obtain the required knowledge and discovery. Their reasoning is limited to interpretation and lack summarized, and therefore not only have to prove the existence of facts, axioms, and not found new theorem, the law and rules. With the in-depth development of artificial intelligence, demonstrated these limitations are becoming even more prominent. It is precisely in such circumstances, machine learning has gradually become one of the core artificial intelligence research. Its application has spread all branches of artificial intelligence, such as expert systems, automated reasoning, natural language understanding, recognition, computer vision, smart robots, and other fields. Which is especially typical expert system knowledge acquisition bottlenecks, people have been trying to use machine learning methods to overcome. Machine learning research is based on physiology, cognitive science understanding of the mechanisms of human learning, human learning process for the establishment of model or models of understanding, the development of learning theory and learning methods, a study of theoretical learning algorithms and analysis, the creation of specific task-oriented applications learning system. These studies aim to promote mutual interaction.