2019年5月23日 (四) 09:43的最后版本

课程参考书

深度学习

Yoshua Bengio, Ian Goodfellow, Aaron Courville, Deep Learning, MIT Press, 2016. DeepLearningBook

Google brain team, TensorFlow: Large-scale machine learning on heterogeneous systems, whitepaper, 2015.

Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. Mining of massive datasets. Cambridge University Press, 2014. MMDS_book

Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.

@@ 第1行： / 第1行： @@
-=== 数据管理 ===
+'''课程参考书'''
-* Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. Mining of massive datasets. Cambridge University Press, 2014. [http://www.mmds.org/ MMDS_book]
-# Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.
-=== 大数据智能 ===
-# 刘知远，崔安欣等，大数据智能：互联网时代的机器学习和自然语言处理技术. 电子工业出版社，2016年。
 = 深度学习 =
@@ 第13行： / 第6行： @@
 # Google brain team, TensorFlow: Large-scale machine learning on heterogeneous systems, whitepaper, 2015.
-=== 计算机围棋 ===
+= 大数据智能 =
-# Mastering the game of Go with deep neural networks and tree search, nature 2015.
+# 刘知远，崔安欣等，大数据智能：互联网时代的机器学习和自然语言处理技术. 电子工业出版社，2016年。
-# Better Computer Go Player with Neural Network and Long-term Prediction, ICLR 2016.
-# Pachi: State of the art open source Go program, Advances in computer games, Springer Berlin Heidelberg, 2011.
+= 数据挖掘 =
-# Training Deep Convolutional Neural Networks to Play Go, JMLR 2015.
+* Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. Mining of massive datasets. Cambridge University Press, 2014. [http://www.mmds.org/ MMDS_book]
+# Vijay Agneeswaran, Real-Time Applications with Storm, Spark, and More Hadoop Alternatives, 2014.