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Python Data Analysis

Python Data Analysis

By : Ivan Idris
3.9 (16)
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Python Data Analysis

Python Data Analysis

3.9 (16)
By: Ivan Idris

Overview of this book

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Table of Contents (17 chapters)
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13
A. Key Concepts
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15
C. Online Resources
16
Index

Appendix A. Key Concepts

This appendix gives a brief overview and glossary of technical concepts used throughout the book.

Amdahl's law predicts the maximum possible speedup due to parallelization. The number of processes limits the absolute maximum speedup. Some parts of any given Python code might be impossible to parallelize. We also have to take into account overhead from parallelization setup and related interprocess communication. Amdahl's law states that there is a linear relationship between the inverse of the speedup, the inverse of the number of processes, and the portion of the code that cannot be parallelized.

ARMA models combine autoregressive and moving average models. They are used to forecast future values of time series.

Artificial Neural Networks (ANN) are models inspired by the animal brain. A neural network is a network of neurons—units with inputs and outputs. The output of a neuron can be passed to a neuron and so on, thus creating a multilayered...

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Python Data Analysis
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