Data Structures & Algorithms in Python is packed with examples, review questions, individual and team exercises, thought experiments, and longer programming projects. It’s ideal for both self-study and classroom settings, and either as a primary text or as a complement to a more formal presentation.
Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.
This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python programming language and its data-oriented library ecosystem and tools that will equip you to become an effective data analyst. While “data analysis” is in the title of the book, the focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis.
Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks.
Recursion has an intimidating reputation: it’s considered to be an advanced computer science topic frequently brought up in coding interviews. But there’s nothing magical about recursion.