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R for Data Analysis in easy steps, 2nd edition is written using a proven easy-to-follow style for maximum appeal. It will be useful to anyone who wants to begin programming in R, with minimum fuss. Updated for the latest version of R.
With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn.
If you're a PHP developer looking for proven solutions to common problems, this cookbook provides code recipes to help you resolve a variety of coding issues.
Entering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience.
“Pure” functional programming, abandoning all the conventional programming techniques, really is difficult.Whether you're looking for a crash course in Functional... Læs mere
The second edition of Python Programming using Problem Solving Approach is designed for undergraduate students of Computer Science Engineering, Information Technology, andComputer... Læs mere
This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming... Læs mere
This book teaches the basics of Oracle GoldenGate, which is simplifies the process of Oracle Database Replication. Its... Læs mere
Parallel processing can be ideally suited for the solving of more complex problems in statistical computing. This book discusses code development in C++ and R, before... Læs mere