本书于2017-07由Packt Publishing出版，作者Christopher Bourez，全书440页。

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通过本书你将学到以下知识

• Get familiar with Theano and deep learning
• Provide examples in supervised, unsupervised, generative, or reinforcement learning.
• Discover the main principles for designing efficient deep learning nets: convolutions, residual connections, and recurrent connections.
• Use Theano on real-world computer vision datasets, such as for digit classification and image classification.
• Extend the use of Theano to natural language processing tasks, for chatbots or machine translation
• Cover artificial intelligence-driven strategies to enable a robot to solve games or learn from an environment
• Generate synthetic data that looks real with generative modeling
• Become familiar with Lasagne and Keras, two frameworks built on top of Theano

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本书的章节

1. THEANO BASICS
2. CLASSIFYING HANDWRITTEN DIGITS WITH A FEEDFORWARD NETWORK
3. ENCODING WORD INTO VECTOR
4. GENERATING TEXT WITH A RECURRENT NEURAL NET
5. ANALYZING SENTIMENT WITH A BIDIRECTIONAL LSTM
6. LOCATING WITH SPATIAL TRANSFORMER NETWORKS
7. CLASSIFYING IMAGES WITH RESIDUAL NETWORKS
8. TRANSLATING AND EXPLAINING WITH ENCODING – DECODING NETWORKS
9. SELECTING RELEVANT INPUTS OR MEMORIES WITH THE MECHANISM OF ATTENTION
10. PREDICTING TIMES SEQUENCES WITH ADVANCED RNN
11. LEARNING FROM THE ENVIRONMENT WITH REINFORCEMENT
12. LEARNING FEATURES WITH UNSUPERVISED GENERATIVE NETWORKS
13. EXTENDING DEEP LEARNING WITH THEANO

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