Buy used Engineering Books online in India
Buy Second Hand Books, Used Books Online In India
Communication System Analog and Digital
Table of contents: introduction signal analysis and transmission amplitude modulation angle modulation probability, random signals and random process noise performance of communication systems radio receivers sampling theory and pulse modulation waveform coding techniques digital multiplexers digital data transmission digital modulation techniques performance analysis of digital communication systems information theory error control coding appendices model question papers for practice index
Hands-On Machine Learning (Aurlien Gron)
A series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details
Mathematics of Machine Learning (Tivadar Dhanka)
Build a solid foundation in the core math behind machine learning algorithms with this comprehensive guide to linear algebra, calculus, and probability, explained through practical Python examples Purchase of the print or Kindle book includes a free PDF eBook Key Features Master linear algebra, calculus, and probability theory for ML Bridge the gap between theory and real-world applications Learn Python implementations of core mathematical concepts Book DescriptionMathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to elevate their technical expertise. With this book, you’ll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts. PhD mathematician turned ML engineer Tivadar Danka—known for his intuitive teaching style that has attracted 100k+ followers—guides you through complex concepts with clarity, providing the structured guidance you need to deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems. Balancing theory with application, this book offers clear explanations of mathematical constructs and their direct relevance to machine learning tasks. Through practical Python examples, you’ll learn to implement and use these ideas in real-world scenarios, such as training machine learning models with gradient descent or working with vectors, matrices, and tensors. By the end of this book, you’ll have gained the confidence to engage with advanced machine learning literature and tailor algorithms to meet specific project requirements. What you will learn Understand core concepts of linear algebra, including matrices, eigenvalues, and decompositions Grasp fundamental principles of calculus, including differentiation and integration Explore advanced topics in multivariable calculus for optimization in high dimensions Master essential probability
Engineering
This acclaimed revision of a classic database systems text offers a complete background in the basics of database design, languages, and system implementation. It provides the latest information combined with real-world examples to help readers master concepts. All concepts are presented in a technically complete yet easy-to-understand style with notations kept to a minimum. A running example of a bank enterprise illustrates concepts at work. To further optimize comprehension, figures and examples, rather than proofs, portray concepts and anticipate results.
