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.
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...
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
This introduction to numerical analysis shows how the mathematics of calculus and linear algebra are implemented in computer algorithms. It develops a deep understanding of why numerical methods work and exactly what their limitations are....
The book constitutes the joint refereed proceedings of the 11th International Conference on Relational Methods in Computer Science, RelMiCS 2009, and the 6th International Conference on Applications of Kleene Algebras, AKA 2009, held in Doha, Qatar in November 2009. The 22 revised full papers presented together with 2 invited papers were...
The main purpose of writing this book is to present a unified approach for automatic
control of atmospheric and space flight vehicles. Such an outlook has become more
necessary nowthan ever,with the advent of aerospace vehicleswhose singlemission
covers operation as aircraft, rocket, and spacecraft at various instants....
Algorithmic Number Theory provides a thorough introduction to the design and analysis of algorithms for problems from the theory of numbers. Although not an elementary textbook, it includes over 300 exercises with suggested solutions. Every theorem not proved in the text or left as an exercise has a reference in the notes section...
