One of my 2018 reservations is reading more books. Here I list some great books in my plan.

Machine Learning

  • Machine Learning: A Probabilistic Perspective
  • Deap Learning(Ian,Goodfellow)
  • Pattern Recognition and Machine Learning(Christopher M Bishop)
  • The elements of statistic learning
  • Hands-On Machine Learning with Scikit-Learn and TensorFlow (in progress now)
  • Python Machine Learning
  • 数学之美
  • 统计学(复习)
  • 统计学习方法
  • 机器学习

Big Data

  • High Performance Spark(review again)
  • Spark The Definitive Guide
  • Kafka The Definitive Guide
  • Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
  • streaming data understanding the real time pipeline
  • Learning Spark Streaming
  • Learning Apache Flink
  • Stream processing with apache flink
  • Architecting HBase Applications
  • HBase Definitive Guide
  • Designing Data-Intensive Applications


  • Programming in Scala(review again)
  • The C++ Programming Language 4th edition
  • High performance Python
  • Getting Starting with R

For my field

  • Gis Fundamentals
  • Computing with Spatial Trajectories