Andrew Ng 深度学习课程系列第五门课程序列模型（Sequence Models）在1月的尾巴终于开课 ，在跳票了几次之后，这门和NLP比较相关的深度学习课程终于开课了。这门课程属于Coursera上的深度学习专项系列 ，这个系列有5门课，目前终于完备，感兴趣的同学可以关注：Deep Learning Specialization
This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others. You will: - Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. - Be able to apply sequence models to natural language problems, including text synthesis. - Be able to apply sequence models to audio applications, including speech recognition and music synthesis. This is the fifth and final course of the Deep Learning Specialization.
这门课程主要面向自然语言，语音和其他序列数据进行深度学习建模，将会学习递归神经网络，GRU，LSTM等内容，以及如何将其应用到语音识别，机器翻译，自然语言理解等任务中去。个人认为这是目前互联网上最适合入门深度学习的系列系列课程了，Andrew Ng 老师善于讲课，另外用Python代码抽丝剥茧扣作业，课程学起来非常舒服，希望最后这门RNN课程也不负众望。参考我之前写得两篇小结：
额外推荐: 深度学习课程资源整理