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Name: 邹台
Type: User
Company: XiDian University
Bio: 计算机专业2017级硕士 研究方向:ML/DL-语音唤醒/语音合成
Location: 陕西,西安
Name: 邹台
Type: User
Company: XiDian University
Bio: 计算机专业2017级硕士 研究方向:ML/DL-语音唤醒/语音合成
Location: 陕西,西安
spring boot 实践学习案例,是 spring boot 初学者及核心技术巩固的最佳实践。另外写博客,用 OpenWrite。
SpringBootStudy
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model
A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model
DeepMind's Tacotron-2 Tensorflow implementation
Code for Temporal Convolution for Real-time Keyword Spotting on Mobile Devices
XDUthesis 西安电子科技大学学位论文模板 Xidian University thesis template
小书匠图床
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