Fluent Python: Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best and possibly most neglected features. Author Luciano Ramalho takes you through Python’s core language features and libraries, … Read more
Linear Models with R: There are many books on regression and analysis of variance. These books expect different levels of preparedness and emphasise the material. This book is not introductory. It presumes some knowledge of basic statistical theory and practice. Readers are expected to know the essentials of statistical inference such as estimation, hypothesis testing … Read more
This book offers an introduction to statistical data analysis by applying the free statistical software R, probably the most powerful statistical software today. The analyses are performed and discussed using real data. After a brief description of the statistical software R, important parameters and diagrams of descriptive statistics are introduced. Subsequently, recommendations for generating diagrams … Read more
This Book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open-source library. If you’re interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages or are curious about a programmer’s perspective on how human language works, you’ll find both fascinating … Read more
An Introduction to R for Quantitative Economics gives an introduction to R to build up graphing, simulating and computing skills so that the reader sees theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free and very flexible and extensible. This book addresses the specific … Read more
What Pythonistas Say About Python Tricks: The Book: ”I love love love the book. It’s like having a seasoned tutor explaining, well, tricks! I’m learning Python on the job and I’m coming from Powershell, which I learned on the job so lots of new, great stuff. Whenever I get stuck in Python (usually with flask … Read more
These notes are an introduction to using the statistical software package R for an introductory statistics course. They are meant to accompany an elementary statistics book such as Kitchens “Exploring Statistics”. The goals are not to show all the features of R, or to replace a standard textbook, but rather to be used with a … Read more
Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naive Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting … Read more
Python for Probability Statistics and Machine Learning 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 in machine learning by working with … Read more
From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
Danielle Navarro, PhD is a computational cognitive scientist at the University of New South Wales. Her research focuses on human concept learning, reasoning and decision-making. She is also interested in language and cultural evolution, cognitive development, and statistical methods in the behavioural sciences
