In today’s fast and competitive world, a program’s performance is just as important to customers as the features it provides. This practical guide teaches developers performance-tuning principles that enable optimization in C++. You’ll learn how to make code that already embodies best practices of C++ design run...

• Build deep learning models with transfer learning principles in Python
• implement transfer learning to solve real-world research...

• Build efficient and concurrent applications in Delphi with focused examples
• Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications.
...

...

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

• Discover high-performing machine learning algorithms and understand how they work in depth
• One-stop solution to mastering supervised, unsupervised, and...

• Master advanced concepts of PostgreSQL 11 with real-world datasets and examples
• Explore query parallelism, data replication, and database performance while working with...

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner....

• Use ensemble methods to improve the performance of predictive analytics models
• Implement feature selection, dimensionality reduction, and cross-validation...