The fast and easy way to learn Python programming and statistics

Python is a general-purpose programming language created in the late 1980s?and named after Monty Python?that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the...

You need much more than imagination to predict earthquakes and detect brain cancer cells. Become an expert in designing and deploying TensorFlow and Keras models, and generate insightful predictions with the power of deep learning.

The presentation and interpretation of (non-relativistic) quantum mechanics is a very well-worked area of study; there have to be very good reasons for adding to the literature on this subject.

My reasons are (obviously) that I am far from satisfied with much of the published work and find difficulties with some points, in...

Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples.

Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian...

An in-depth review of key techniques in software error detection

Software error detection is one of the most challenging problems in software engineering. Now, you can learn how to make the most of software testing by selecting test cases to maximize the probability of revealing latent errors. Software Error Detection through...

Unleash the power of Python for your data analysis projectswith For Dummies!

Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to...

Introductory Probability is a pleasure to read and provides a fine answer to the question: How do you construct Brownian motion from scratch, given that you are a competent analyst? There are at least two ways to develop probability theory. The more familiar path is to treat it as its own discipline, and work from intuitive examples such as...

In today’s world, analytical thinking is a critical part of any solid education. An important segment of this kind of reasoning—one that cuts across many disciplines—is discrete mathematics. Discrete math concerns counting, probability, (sophisticated forms of) addition, and limit processes over discrete sets. Combinatorics, graph...

"Quantum Computing without Magic gives a refreshing and down to earth approach to quantum information as well as quantum devices which will have a fundamental impact on the technology of the 21st century." —Raymond Laflamme, Canada Research Chair in Quantum Information, and Director, Institute for...

"Paul Nahin's Digital Dice is a marvelous book, one that is even better than his Duelling Idiots. Nahin presents twenty-one great probability problems, from George Gamow's famous elevator paradox (as corrected by Donald Knuth) to a bewildering puzzle involving two rolls of toilet paper, and he solves them all with the aid...

Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book...