𝔖 Scriptorium

✦ LIBER ✦

📁

Python for Probability, Statistics, and Machine Learning

✍ Scribed by José Unpingco (auth.)

Publisher: Springer International Publishing
Year: 2016
Tongue: English
Leaves: 288
Edition: 1
Category: Library

⬇ Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.

✦ Table of Contents

Front Matter....Pages i-xv
Getting Started with Scientific Python....Pages 1-33
Probability....Pages 35-100
Statistics....Pages 101-196
Machine Learning....Pages 197-273
Back Matter....Pages 275-276

✦ Subjects

Communications Engineering, Networks; Appl.Mathematics/Computational Methods of Engineering; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Probability and Statistics in Computer Science; Data Mining

📜 SIMILAR VOLUMES

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning

✍ José Unpingco 📂 Library 📅 2016 🏛 Springer 🌐 English

This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions i

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning

✍ José Unpingco 📂 Library 📅 2022 🏛 Springer 🌐 English

<p><span>Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning

✍ Jose Unpingco 📂 Library 📅 2016 🏛 Springer 🌐 English

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning

✍ Unpingco J. 📂 Library 🌐 English

Springer, 2016. — 276 p. — ISBN: 3319307150<div class="bb-sep"></div>Explains how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methods<br/>Connects to key open-source Python communities and corresponding modules focused on the latest developments

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning, 2nd Edition

✍ José Unpingco 📂 Library 📅 2018 🏛 Springer 🌐 English

<div> <p>This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key i

Python for Probability, Statistics, and

📁 Python for Probability, Statistics, and Machine Learning 2nd Ed.

✍ José Unpingco 📂 Library 📅 2019 🏛 Springer 🌐 English

This textbook, fully updated to feature Python version 3.7, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jup