Marknadens största urval
Snabb leverans

Böcker utgivna av APress

Filter
Filter
Sortera efterSortera Populära
  • - Implementing Predictive Models and Machine Learning Techniques
    av Deepti Gupta
    861

    Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.

  • - Handle Data-Driven Challenges in an Enterprise Big Data Lake
    av Saurabh Gupta & Venkata Giri
    777

  • - Accelerated Web Development with Ruby on Rails
    av Stefan Wintermeyer
    941

  • - Chatbots and Face, Object, and Speech Recognition With TensorFlow and Keras
    av Navin Kumar Manaswi
    847

  • - Building a Next-Generation Application from the Ground Up
    av Nishith Pathak & Anurag Bhandari
    847

  • - Quick Start to Agile Scrum Methodology and the Scrum Master Role
    av Ilya Bibik
    311

  • - A Continuous Improvement Journey
    av Navid Nader-Rezvani
    447

  • - Building Fun Programs, Games, and Electronic Projects
    av Bob Dukish
    847

    The projects will be described where the program code that is presented can be modified, or in which two or more of the sample programs may be used to synthesize a new program as the solution to the problem that is presented.

  • - A Non-Technical Project-Based Introduction
    av Richard McKeon
    377

  • - An In-Depth Guide to Windows PowerShell DSC
    av Ravikanth Chaganti
    1 141

  • av Adam Freeman
    861

  • - Using pandas, Requests, and Recurrent
    av Max Humber
    687

  • - Cases Studies from Healthcare, Retail, and Finance
    av Puneet Mathur
    881

  • - Learn to Build Single Page Applications in Vue from Scratch
    av Brett Nelson
    741

  • - Creating Neural Networks with Python
    av Karan Jain, Palash Goyal & Sumit Pandey
    801

  • - SQL and NoSQL Data Storage Using MySQL for Python Programmers
    av Jesper Wisborg Krogh
    861

  • - With Packer, Terraform, Ansible, and Vagrant
    av Oscar Medina & Ethan Schumann
    547

  • - Migrating to Azure Cosmos DB and Using the MongoDB API
    av Manish Sharma
    511

  • - Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
    av Wee Hyong Tok, Mathew Salvaris & Danielle Dean
    801

  • - C# Programming for Windows 10
    av Abhishek Nandy & Manisha Biswas
    531

    Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform.

  • - A Comprehensive Guidebook to Growing Your Net Worth
    av Keith R. Fevurly
    547

  • - A Beginner's Guide to Building Blockchain Solutions
    av Priyansu Sekhar Panda, Bikramaditya Singhal & Gautam Dhameja
    681

  • - Autoencoding in the Complex Domain
    av Timothy Masters
    681

  • - Using the Scala API
    av Subhashini Chellappan & Dharanitharan Ganesan
    847

  • - Building Effective Vulnerability Management Strategies to Protect Organizations
    av Morey J. Haber & Brad Hibbert
    547

  • - A Statistical Battle Against Project Obstacles
    av Mario Vanhoucke
    627

    Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools.The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles.Data-driven project management is known in the academic literature as "e;dynamic scheduling"e; or "e;integrated project management and control."e; It is a project management methodology to plan, monitor, and control projects in progress in order to deliver them on time and within budget to the client. Its main focus is on the integration of three crucial aspects, as follows:Baseline Scheduling: Plan the project activities to create a project timetable with time and budget restrictions. Determine start and finish times of each project activity within the activity network and resource constraints. Know the expected timing of the work to be done as well as an expected impact on the project's time and budget objectives. Schedule Risk Analysis: Analyze the risk of the baseline schedule and its impact on the project's time and budget. Use Monte Carlo simulations to assess the risk of the baseline schedule and to forecast the impact of time and budget deviations on the project objectives. Project Control: Measure and analyze the project's performance data and take actions to bring the project on track. Monitor deviations from the expected project progress and control performance in order to facilitate the decision-making process in case corrective actions are needed to bring projects back on track. Both traditional Earned Value Management (EVM) and the novel Earned Schedule (ES) methods are used.What You'll LearnImplement a data-driven project management methodology (also known as "e;dynamic scheduling"e;) which allows project managers to plan, monitor, and control projects while delivering them on time and within budgetStudy different project management tools and techniques, such as PERT/CPM, schedule risk analysis (SRA), resource buffering, and earned value management (EVM)Understand the three aspects of dynamic scheduling: baseline scheduling, schedule risk analysis, and project controlWho This Book Is ForProject managers looking to learn data-driven project management (or "e;dynamic scheduling"e;) via a novel, demonstrating real-time simulations of how project managers can solve common project obstacles

  • - Creating Amazing Graphics with Open Source Software
    av Peter Spath
    511

    Learn advanced techniques and improve your audio visualization skills with Thinking Machine Audio Dreams (ThMAD). With this book, you can concentrate on advanced examples and usage patterns, including using shaders in a more profound way, and how to incorporate ThMAD into a tool chain using the professional sound server JACK.Advanced Audio Visualization Using ThMAD provides advanced techniques for generating graphics, improving performance, and providing readers with the skills needed to create more interesting visualizations. You will also learn professional setups with highly developed visual and aural art tool chains.What You'll LearnUse the ThMAD software for advanced setups in their personal and professional projectsGain a pragmatic introduction to using shadersUse JACK sound servers with ThMADControl the timing ThMADWork with advanced configurationsWho This Book Is ForArtists and developers already familiar with ThMAD and looking to enhance their projects. In addition, readers primarily interested in using shaders or the Jack audio server for graphics generation can benefit from the book as well.

  • - Improving Programming Skills with Examples in Python
    av Michael Stueben
    571

    Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more. Taking an informal, conversational tone, author Michael Stueben offers programming stories, anecdotes, observations, advice, tricks, examples, and challenges based on his 38 years experience writing code and teaching programming classes. Trying to teach style to beginners is notoriously difficult and can easily appear pedantic. Instead, this book offers solutions and many examples to back up his ideas. Good Habits for Great Coding distills Stueben's three decades of analyzing his own mistakes, analyzing student mistakes, searching for problems that teach lessons, and searching for simple examples to illustrate complex ideas.  Having found that most learn by trying out challenging problems, and reflecting on them, each chapter includes quizzes and problems. The final chapter introduces dynamic programming to reduce complex problems to subcases, and illustrates many concepts discussed in the book. Code samples are provided in Python and designed to be understandable by readers familiar with any modern programming language. At the end of this book, you will have acquired a lifetime of good coding advice, the lessons the author wishes he had learned when he was a novice.What You'll LearnCreate readable code through examples of good and bad styleWrite difficult algorithms by comparing your code to the author's codeDerive and code difficult algorithms using dynamic programmingUnderstand the psychology of the coding processWho This Book Is ForStudents or novice programmers who have taken a beginning programming course and understand coding basics. Teachers will appreciate the author's road-tested ideas that they may apply to their own teaching.

  • - A Guide to Machine Learning Engineering
    av Geoff Hulten
    801

    Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success.This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You'll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for successDesign an intelligent user experience: Produce data to help make the Intelligent System better over timeImplement an Intelligent System: Execute, manage, and measure Intelligent Systems in practiceCreate intelligence: Use different approaches, including machine learningOrchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

Gör som tusentals andra bokälskare

Prenumerera på vårt nyhetsbrev för att få fantastiska erbjudanden och inspiration för din nästa läsning.