python 深度学习

Python深度学习-简介 (Python Deep Learning - Introduction)

Deep structured learning or hierarchical learning or deep learning in short is part of the family of machine learning methods which are themselves a subset of the broader field of Artificial Intelligence.

深度结构化学习或分层学习或简称为深度学习是机器学习方法家族的一部分，而机器学习方法本身就是更广泛的人工智能领域的子集。

Deep learning is a class of machine learning algorithms that use several layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input.

深度学习是一类机器学习算法，它使用几层非线性处理单元进行特征提取和转换。 每个后续层都使用前一层的输出作为输入。

Deep neural networks, deep belief networks and recurrent neural networks have been applied to fields such as computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, and bioinformatics where they produced results comparable to and in some cases better than human experts have.

深度神经网络，深度信念网络和递归神经网络已应用于计算机视觉，语音识别，自然语言处理，音频识别，社交网络过滤，机器翻译和生物信息学等领域，在这些领域所产生的结果可与之媲美，在某些情况下比人类专家要好。

Deep Learning Algorithms and Networks −

深度学习算法和网络-

• are based on the unsupervised learning of multiple levels of features or representations of the data. Higher-level features are derived from lower level features to form a hierarchical representation.

  基于无监督学习数据的多个级别的特征或表示形式。 较高级别的功能从较低级别的功能派生而来，形成了层次表示。

• use some form of gradient descent for training.

  使用某种形式的梯度下降进行训练。

翻译自: https://www.tutorialspoint.com/python_deep_learning/python_deep_learning_introduction.htm

python 深度学习