Recent few years, I kept a habit to study a couple of topics and read 5 to 8 technical books per year. Below are the technical books, I have read or plan to read.
2018: Deep Learning, PyTorch, Tensorflow
| Book Name | Start Month | End Month |
|---|---|---|
| Deep Learning with Python | Jan | Jan |
| Deep Learning (Yoshua Bengio Ch 7-11) | Feb | Mar |
| Natural Language Processing with PyTorch |
2017: Docker, Python, Deep Learning
| Book Name | Start Month | End Month |
|---|---|---|
| Blockchain Specs: Ethereum, Hyperledger | Jan | Feb |
| Java 8 in Action | Mar | Apr |
| Docker in Action | May | May |
| Natural Language Processing with Python | Jun | Jun |
| Advanced Analytics with Spark, 2nd | Jul | Jul |
| Flask Web Development, 2nd | Aug | Aug |
| Deep Learning Specialization (Andrew Ng) | Sept | Oct |
| Fast.ai: Practical Deep Learning For Coders, Part I | Oct | Nov |
| Deep Learning (Yoshua Bengio Ch 1-6) | Oct | Nov |
| Hands-On Machine Learning with Scikit-Learn and TensorFlow (Part II) | Nov | Dec |
2016: Scala, Spark, Kafka, Akka
| Book Name | Start Month | End Month |
|---|---|---|
| Programming Scala, 2nd | Jan | Feb |
| Scala Functional Programming Patterns | Apr | Jun |
| Machine Learning with Spark | July | Aug |
| Kafka the Definitive Guide | Sep | Oct |
| Akka in Action | Nov | Dec |