Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms. This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included. Deep Learning with Python also introduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. What You Will Learn Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe Gain the fundamentals of deep learning with mathematical prerequisites Discover the practical considerations of large scale experiments Take deep learning models to production Who This Book Is For Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
An indispensable collection of practical tips and real-world advice for tackling common Python problems and taking your code to the next level. Features interviews with high-profile Python developers who share their tips, tricks, best practices, and real-world advice gleaned from years of experience. Sharpen your Python skills as you dive deep into the Python programming language with Serious Python. You´ll cover a range of advanced topics like multithreading and memorization, get advice from experts on things like designing APIs and dealing with databases, and learn Python internals to help you gain a deeper understanding of the language itself. Written for developers and experienced programmers, Serious Python brings together over 15 years of Python experience to teach you how to avoid common mistakes, write code more efficiently, and build better programs in less time. As you make your way through the book´s extensive tutorials, you´ll learn how to start a project and tackle topics like versioning, layouts, coding style, and automated checks. You´ll learn how to package your software for distribution, optimize performance, use the right data structures, define functions efficiently, pick the right libraries, build future-proof programs, and optimize your programs down to the bytecode. You´ll also learn how to: - Make and use effective decorators and methods, including abstract, static, and class methods - Employ Python for functional programming using generators, pure functions, and functional functions - Extend flake8 to work with the abstract syntax tree (AST) to introduce more sophisticated automatic checks into your programs - Apply dynamic performance analysis to identify bottlenecks in your code - Work with relational databases and effectively manage and stream data with PostgreSQL If you´ve been looking for a way to take your Python skills from good to great, Serious Python will help you get there. Learn from the experts and get seriously good at Python with Serious Python!
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models. All major classical techniques: Mean/Least-Squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods. The latest trends: Sparsity, convex analysis and optimization, online distributed algorithms, learning in RKH spaces, Bayesian inference, graphical and hidden Markov models, particle filtering, deep learning, dictionary learning and latent variables modeling. Case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, show how the theory can be applied. MATLAB code for all the main algorithms are available on an accompanying website, enabling the reader to experiment with the code.
The go-to MCSA prep guide, updated for Windows 10 and the new exams MCSA Windows 10 Complete Study Guide is your comprehensive resource for taking both Exams 70-698 and 70-697. Covering 100% of all exam objectives, this study guide goes beyond mere review to delve deeper into the complex topics and technologies to help you strengthen your understanding and sharpen your skills. Written by a veteran Microsoft MVP, this guide walks you through MCSA skills in context to show you how concepts are applied in real-world situations. Hands-on exercises speed the learning process and facilitate internalization, while review questions challenge and test the depth of your understanding. You also get access to the Sybex interactive online learning environment, featuring flashcards, videos, an assessment test, and bonus practice exams to face exam day with confidence. The MCSA certification process has changed; Exam 70-698 tests your skills in installing and configuring Windows 10, and then Exam 70-697 gauges your abilities in configuring Windows devices. This book is your ideal companion to study for both exams. Study 100 percent of the objectives for Exams 70-698 and 70-697 Apply your knowledge with hands-on exercises Test your skills with challenging review questions Access videos, electronic flashcards, a searchable glossary, and bonus practice exams The demand for qualified Windows 10 professionals will be high, as more than half of the corporate user base that skipped Windows 8/8.1 is expected to adopt Windows 10. If you want the skills that are in demand, you need to get certified; if you´re ready to get serious about the exam, MCSA: Windows 10 Complete Study Guide is the resource you shouldn´t be without.
This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of ´´boosting,´´ how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. This revised edition contains three entirely new chapters on critical topics regarding the pragmatic application of machine learning in industry. The chapters examine multi-label domains, unsupervised learning and its use in deep learning, and logical approaches to induction. Numerous chapters have been expanded, and the presentation of the material has been enhanced. The book contains many new exercises, numerous solved examples, thought-provoking experiments, and computer assignments for independent work.
Deliver bug-free software projects on schedule and within budget Get a clear, complete understanding of how to estimate software costs, schedules, and quality using the real-world information contained in this comprehensive volume. Find out how to choose the correct hardware and software tools, develop an appraisal strategy, deploy tests and prototypes, and produce accurate software cost estimates. Plus, you´ll get full coverage of cutting-edge estimating approaches using Java, object-oriented methods, and reusable components. * Plan for and execute project-, phase-, and activity-level cost estimations * Estimate regression, component, integration, and stress tests * Compensate for inaccuracies in data collection, calculation, and analysis * Assess software deliverables and data complexity * Test design principles and operational characteristics using software prototyping * Handle configuration change, research, quality control, and documentation costs ´´Capers Jones´ work offers a unique contribution to the understanding of the economics of software production. It provides deep insights into why our advances in computing are not matched with corresponding improvements in the software that drives it. This book is absolutely required reading for an understanding of the limitations of our technological advances.´´ --Paul A. Strassmann, former CIO of Xerox, the Department of Defense, and NASA
This updated edition of Michael W. Lucas´ definitive volume on FreeBSD-based systems adds coverage of modern disks, the ZFS filesystem IPv6, redesigned jail and packaging systems, and virtualization, among dozens of new features added in the last 10 years. FreeBSD is the muscle behind companies like Netflix and EMC. Any place where someone does heavy lifting on the Internet, you´ll find FreeBSD. This newly revised edition of Absolute FreeBSD brings FreeBSD´s strengths to bear on your problems and covers FreeBSD´s newest features, all in the inimitable style that has made author Michael W. Lucas´ system administration books so popular. Any computer system is only as good as the system administrator´s knowledge. Absolute FreeBSD teaches you everything you need to know about managing FreeBSD systems, from installation, configuration, and taking the system from ´´just working´´ to ´´working well.´´ A cohesive focus on service delivery and best practice means that you can apply much of the book to other operating systems. Absolute FreeBSD dives deep into server management, taking you beyond just making things work and into understanding why they work. You´ll learn: How to best install FreeBSD to meet your needs Which filesystem to use in your environment How to back up and restore critical data How to tweak the kernel, and when not to Network configuration, from activating interfaces to selecting congestion control algorithms How to manage UFS, ZFS, and other critical filesystems FreeBSD´s software packaging system, including how to build your own package repository How and when to upgrade Techniques to build your own FreeBSD Advanced security features like blacklistd and packet filtering How to monitor and adjust performance Container-style virtualization with jails Diskless systems Panic management and bug reporting With Absolute FreeBSD readers will get the solid introduction they need while fans of the earlier editions will expand their skills even further.
Test your knowledge and prepare for the OCA/OCP exams OCA/OCP Java SE 8 Programmer Practice Tests complements the Sybex OCA: Oracle Certified Associate Java SE 8 Programmer I Certification Study Guide and the OCP: Oracle Certified Professional Java SE 8 Programmer II Study Guide for exams 1Z0-808 and 1ZO-809 by providing last minute review of 100% of exam objectives. Get the advantage of over 1,000 expert crafted questions that not only provide the answer, but also give detailed explanations. You will have access to unique practice questions that cover all 21 objective domains in the OCA/OCP exams in the format you desire--test questions can also be accessed via the Sybex interactive learning environment. Two additional practice exams will ensure that you are ready for exam day. Whether you have studied with Sybex study guides for your OCA/OCP or have used another brand, this is your chance to test your skills. Access to all practice questions online with the Sybex interactive learning environment Over 1,000 unique practice questions and 2 practice exams include expert explanations Covers 100% of all 21 OCA/OCP objective domains for Exams 1Z0-809 and 1Z0-809 Studying the objectives are one thing, but diving deeper and uncovering areas where further attention is needed can increase your chance of exam day success. Full coverage of all domains shows you what to expect on exam day, and accompanying explanations help you pinpoint which objectives deserve another look.
Learn the basics of serverless computing and how to develop event-driven architectures with the three major cloud platforms: Amazon Web Services, Microsoft Azure, and Google Cloud. This hands-on guide dives into the foundations of serverless computing, its use cases, and how to apply it using developer tools such as Node.js, Visual Studio Code, Postman, and Serverless Framework. You will apply the fundamentals of serverless technology from the ground up, and come away with a greater understanding of its power and how to make it work for you. This book teaches you how to quickly and securely develop applications without the hassle of configuring and maintaining infrastructure. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon completion, you will have the knowledge and resources to build your own serverless application hosted in AWS, Azure, or Google Cloud and will have experienced the benefits of event-driven technology for yourself. What You´ll Learn Gain a deeper understanding of serverless computing and when to use it Use development tools such as Node.js, Postman, and VS code to quickly set up your serverless development environment and produce applications Apply triggers to your serverless functions that best suit the architecture for the problem the functions are solving Begin building applications across cloud providers that utilize the power of serverless technology Understand best development practices with serverless computing to maintain scalable and practical solutions Code with an agnostic approach to cloud providers to minimize provider dependency Who This Book Is For Any developer looking to expand current knowledge of serverless computing, its applications, and how to architect serverless solutions, or someone just beginning in these areas