… code smells. The built dataset contains 1,000 samples for each code smell, with 18 features
extracted from the source code… of six machine learning models as baselines in Python code …

… this work as a citation and/or a potential source of further information does not mean that the
… For many years, traditional desktop and web programming have dominated the landscape, …

… using natural language processing, deep learning, and traditional statistical methods. He …
The focus of this chapter is on TensorFlow 2.0, an open source Python library that allows us …

… to the Python coding guidelines and numpy style documentation. BSD licensing. Most of the
… Python ecosystem, it can easily be integrated into applications outside the traditional range …

… Any source code or other supplementary material referenced by the author in this book is
available to readers on GitHub via the book’s product page, located at www.apress.com/978-1-…

… a Deep Learning Neural Network (DLNN) model in landslide susceptibility assessments and
compare its predictive performance with state-of-the-art machine learning models… (source of …

… learning libraries, this book also introduces the mathematical concepts behind machine
learning algorithms… with programming in Python to follow along with the code examples we …

… targets is to exploit this data source for the rapid … machine learning model using the three
category of methods described in Section 2. The entire process is implemented here in Python …

… and are used in conventional statistical models like those for regression and classification. …
In the following snippet (Figure 5), we show the code to perform a 3-fold cross-validation for …

… of these technologies over more traditional approaches is a lack … and tools for making
machine learning models and their … implementations for deep learning, since Python code is only …