AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
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Sep 14, 2020 - Python
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AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
Build your neural network easy and fast
Tensorflow tutorial from basic to hard
深度学习入门教程, 优秀文章, Deep Learning Tutorial
CNN-RNN中文文本分类,基于TensorFlow
中文古诗自动作诗机器人,屌炸天,基于tensorflow1.10 api,正在积极维护升级中,快star,保持更新!
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
Deep learning driven jazz generation using Keras & Theano!
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
Speech synthesis, voice conversion, self-supervised learning, music generation,Automatic Speech Recognition, Speaker Verification, Speech Synthesis, Language Modeling
1st place solution
Recurrent neural network for audio noise reduction
Multi-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.
Datasets, tools, and benchmarks for representation learning of code.
TensorFlow Tutorial for Time Series Prediction
Overview of Modern Deep Learning Techniques Applied to Natural Language Processing
Sentiment Analysis with LSTMs in Tensorflow
Data augmentation for NLP, presented at EMNLP 2019
Chatbot in 200 lines of code using TensorLayer
Tensorflow implementation of attention mechanism for text classification tasks.
Sequence to Sequence Models with PyTorch
CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017
RNN based Time-series Anomaly detector model implemented in Pytorch.
Stock Price Prediction using Machine Learning Techniques
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Hi I would like to propose a better implementation for 'test_indices':
We can remove the unneeded np.array casting:
Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))
Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))