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
- 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