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python教程,包括:python基础、python进阶;常用机器学习库:numpy、scipy、sklearn、xgboost;深度学习库:keras、tensorflow、paddle、pytorch。

License: Apache License 2.0

Python 9.84% Jupyter Notebook 86.30% HTML 1.07% JavaScript 0.40% CSS 2.38% Shell 0.01%

python-tutorial's Introduction

python-tutorial-exercise

python教程,包括:python基础、numpy、scipy、python进阶、matplotlib、OOP、tensorflow、keras、pandas、NLP analysis.

07keras

  • bAbi: 阅读理解任务
  • 记忆网络(memory network)实现阅读理解任务
  • RNN网络实现
  • keras 应用
  • 01.base: 认识keras变量
  • 02mlp_multi_classification: 多层感知器多分类深度网络
  • 03mlp_binary_classification: 多层感知器二分类深度网络
  • 04vgg_conv: VGG,图像经典卷积网络结构
  • 05lstm_classification: LSTM分类网络
  • 06sequential: 序列模型,模型保存
  • 07shared_lstm: 模型参数共享
  • 08imdb_fasttext: fasttext网络结构实现二分类
  • 09fasttext_multi_classification: fasttext的深度网络结构实现多分类
  • 10seq2seq: 法语到英语的翻译任务,seq2seq模型
  • 11lstm_text_generation: LSTM模型实现文本生成任务
  • 12rnn_num_add: RNN网络学习三位数以内的加法运算
  • 13rnn_num_multiplication: RNN网络学习三位数以内的乘法运算

19xgboost

文本特征分类

lr.py lr 文本分类

xgb.py xgboost 文本分类

xgb_lr.py xgboost 提取特征之间的关系,再用lr文本分类

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