Other data science topics we didn't cover
Although we covered the data science foundation and much of the tools we need for basic data science, we couldn't cover everything. Some of the topics we left uncovered are:
- Recommender systems
- Networks and graph analysis
- Machine learning explainability
- Test-driven development (TDD)
- Reinforcement learning
- Neural networks
Recommender systems were mentioned in the book, and are used to recommend things like products, movies, or articles to people. They can be based on previous preferences of a user or combine data from many users. Packt does have one book on recommender systems in Python, Hands-On Recommendation Systems with Python by Rounak Banik. There are also many other resources out there for learning recommendation systems and creating and maintaining recommender systems can be an important job that can take one or several people to accomplish.
Graph analysis encompasses networks...
