o'reilly media PDF: 1 to 10 of 100 results fetched - page 1 [an]

The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change

https://www.amazon.com/Managers-Path-Leaders-Navigating-Grow...
Managing people is difficult wherever you work. But in the tech industry, where management is also a technical discipline, the learning curve can be brutal—especially when there are few tools, texts, and frameworks to help you. In this practical guide, author Camille Fournier (tech lead turned CTO) takes you through each stage in the journey from engineer to technical manager.From mentoring interns to working with senior staff, you’ll get actionable advice for approaching various obstacles in your path. This book is ideal whether you’re a new manager, a mentor, or a more experienced leader looking for fresh advice. Pick up this book and learn how to become a better manager and leader in your organization.
  • Begin by exploring what you expect from a manager
  • Understand what it takes to be a good mentor, and a good tech lead
  • Learn how to manage individual members while remaining focused on the entire team
  • Understand how to manage yourself and avoid common pitfalls that challenge many leaders
  • Manage multiple teams and learn how to manage managers
  • Learn how to build and bootstrap a unifying culture in teams
Published by: O'Reilly Media | Publication date: 03/13/2017
Kindle book details: Kindle Edition, 244 pages

Learning Python: Powerful Object-Oriented Programming

https://www.amazon.com/Learning-Python-Powerful-Object-Orien...
Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages.Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.
  • Explore Python’s major built-in object types such as numbers, lists, and dictionaries
  • Create and process objects with Python statements, and learn Python’s general syntax model
  • Use functions to avoid code redundancy and package code for reuse
  • Organize statements, functions, and other tools into larger components with modules
  • Dive into classes: Python’s object-oriented programming tool for structuring code
  • Write large programs with Python’s exception-handling model and development tools
  • Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing
Author: Mark Lutz
Published by: O'Reilly Media | Publication date: 06/12/2013
Kindle book details: Kindle Edition, 1650 pages

The Customer-Driven Playbook: Converting Customer Feedback into Successful Products

https://www.amazon.com/Customer-Driven-Playbook-Converting-C...
Despite the wide acceptance of Lean approaches and customer-development strategies, many product teams still have difficulty putting these principles into meaningful action. That’s where The Customer-Driven Playbook comes in. This practical guide provides a complete end-to-end process that will help you understand customers, identify their problems, conceptualize new ideas, and create fantastic products they’ll love.To build successful products, you need to continually test your assumptions about your customers and the products you build. This book shows team leads, researchers, designers, and managers how to use the Hypothesis Progression Framework (HPF) to formulate, experiment with, and make sense of critical customer and product assumptions at every stage. With helpful tips, real-world examples, and complete guides, you’ll quickly learn how to turn Lean theory into action.
  • Collect and formulate your assumptions into hypotheses that can be tested to unlock meaningful insights
  • Conduct experiments to create a continual cadence of learning
  • Derive patterns and meaning from the feedback you’ve collected from customers
  • Improve your confidence when making strategic business and product decisions
  • Track the progression of your assumptions, hypotheses, early ideas, concepts, and product features with step-by-step playbooks
  • Improve customer satisfaction by creating a consistent feedback loop
Published by: O'Reilly Media | Publication date: 06/20/2017
Kindle book details: Kindle Edition, 254 pages

Designing Bots: Creating Conversational Experiences

https://www.amazon.com/Designing-Bots-Creating-Conversationa...
From Facebook Messenger to Kik, and from Slack bots to Google Assistant, Amazon Alexa, and email bots, the new conversational apps are revolutionizing the way we interact with software. This practical guide shows you how to design and build great conversational experiences and delightful bots that help people be more productive, whether it’s for a new consumer service or an enterprise efficiency product.Ideal for designers, product managers, and entrepreneurs, this book explores what works and what doesn’t in real-world bot examples, and provides practical design patterns for your bot-building toolbox. You’ll learn how to use an effective onboarding process, outline different flows, define a bot personality, and choose the right balance of rich control and text.
  • Explore different bot use-cases and design best practices
  • Understand bot anatomy—such as brand and personality, conversations, advanced UI controls—and their associated design patterns
  • Learn steps for building a Facebook Messenger consumer bot and a Slack business bot
  • Explore the lessons learned and shared experiences of designers and entrepreneurs who have built bots
  • Design and prototype your first bot, and experiment with user feedback
Author: Amir Shevat
Published by: O'Reilly Media | Publication date: 05/17/2017
Kindle book details: Kindle Edition, 348 pages

Cloud Foundry: The Definitive Guide: Develop, Deploy, and Scale

https://www.amazon.com/Cloud-Foundry-Definitive-Develop-Depl...
How can Cloud Foundry help you develop and deploy business-critical applications and tasks with velocity? This practical guide demonstrates how this open source, cloud-native application platform not only significantly reduces the develop-to-deploy cycle time, but also raises the value line for application operators by changing the way applications and supporting services are deployed and run. Learn how Cloud Foundry can help you improve your product velocity by handling many of essential tasks required to run applications in production.Author Duncan Winn shows DevOps and operations teams how to configure and run Cloud Foundry at scale. You’ll examine Cloud Foundry’s technical concepts—including how various platform components interrelate—and learn how to choose your underlying infrastructure, define the networking architecture, and establish resiliency requirements.This book covers:
  • Cloud-native concepts that make the app build, test, deploy, and scale faster
  • How to deploy Cloud Foundry and the BOSH release engineering toolchain
  • Concepts and components of Cloud Foundry’s runtime architecture
  • Cloud Foundry’s routing mechanisms and capabilities
  • The platform’s approach to container tooling and orchestration
  • BOSH concepts, deployments, components, and commands
  • Basic tools and techniques for debugging the platform
  • Recent and soon-to-emerge features of Cloud Foundry
Published by: O'Reilly Media | Publication date: 05/24/2017
Kindle book details: Kindle Edition, 324 pages

Terraform: Up and Running: Writing Infrastructure as Code

https://www.amazon.com/Terraform-Running-Writing-Infrastruct...
Terraform has emerged as a key player in the DevOps world for defining, launching, and managing infrastructure as code (IAC) across a variety of cloud and virtualization platforms, including AWS, Google Cloud, and Azure. This hands-on book is the fastest way to get up and running with Terraform.Gruntwork co-founder Yevgeniy (Jim) Brikman walks you through dozens of code examples that demonstrate how to use Terraform’s simple, declarative programming language to deploy and manage infrastructure with just a few commands. Whether you’re a novice developer, aspiring DevOps engineer, or veteran sysadmin, this book will take you from Terraform basics to running a full tech stack capable of supporting a massive amount of traffic and a large team of developers.
  • Compare Terraform to other IAC tools, such as Chef, Puppet, Ansible, and Salt Stack
  • Use Terraform to deploy server clusters, load balancers, and databases
  • Learn how Terraform manages the state of your infrastructure and how it impacts file layout, isolation, and locking
  • Create reusable infrastructure with Terraform modules
  • Try out advanced Terraform syntax to implement loops, if-statements, and zero-downtime deployment
  • Use Terraform as a team, including best practices for writing, testing, and versioning Terraform code
Published by: O'Reilly Media | Publication date: 03/13/2017
Kindle book details: Kindle Edition, 206 pages

Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-T...
Graphics in this book are printed in black and white.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, 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 a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.
  • Explore the machine learning landscape, particularly neural nets
  • Use scikit-learn to track an example machine-learning project end-to-end
  • Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
  • Use the TensorFlow library to build and train neural nets
  • Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
  • Learn techniques for training and scaling deep neural nets
  • Apply practical code examples without acquiring excessive machine learning theory or algorithm details
Published by: O'Reilly Media | Publication date: 03/13/2017
Kindle book details: Kindle Edition, 570 pages

Zero Trust Networks: Building Secure Systems in Untrusted Networks

https://www.amazon.com/Zero-Trust-Networks-Building-Untruste...
The perimeter defenses guarding your network perhaps are not as secure as you think. Hosts behind the firewall have no defenses of their own, so when a host in the "trusted" zone is breached, access to your data center is not far behind. That’s an all-too-familiar scenario today. With this practical book, you’ll learn the principles behind zero trust architecture, along with details necessary to implement it.The Zero Trust Model treats all hosts as if they’re internet-facing, and considers the entire network to be compromised and hostile. By taking this approach, you’ll focus on building strong authentication, authorization, and encryption throughout, while providing compartmentalized access and better operational agility.
  • Understand how perimeter-based defenses have evolved to become the broken model we use today
  • Explore two case studies of zero trust in production networks on the client side (Google) and on the server side (PagerDuty)
  • Get example configuration for open source tools that you can use to build a zero trust network
  • Learn how to migrate from a perimeter-based network to a zero trust network in production
Published by: O'Reilly Media | Publication date: 06/19/2017
Kindle book details: Kindle Edition, 240 pages

Thoughtful Machine Learning with Python: A Test-Driven Approach

https://www.amazon.com/Thoughtful-Machine-Learning-Python-Te...
Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.Featuring graphs and highlighted code examples throughout, the book features tests with Python’s Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you’re a software engineer or business analyst interested in data science, this book will help you:
  • Reference real-world examples to test each algorithm through engaging, hands-on exercises
  • Apply test-driven development (TDD) to write and run tests before you start coding
  • Explore techniques for improving your machine-learning models with data extraction and feature development
  • Watch out for the risks of machine learning, such as underfitting or overfitting data
  • Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms
Author: Matthew Kirk
Published by: O'Reilly Media | Publication date: 01/16/2017
Kindle book details: Kindle Edition, 216 pages

Practical Statistics for Data Scientists: 50 Essential Concepts

https://www.amazon.com/Practical-Statistics-Data-Scientists-...
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you’ll learn:
  • Why exploratory data analysis is a key preliminary step in data science
  • How random sampling can reduce bias and yield a higher quality dataset, even with big data
  • How the principles of experimental design yield definitive answers to questions
  • How to use regression to estimate outcomes and detect anomalies
  • Key classification techniques for predicting which categories a record belongs to
  • Statistical machine learning methods that “learn” from data
  • Unsupervised learning methods for extracting meaning from unlabeled data
Published by: O'Reilly Media | Publication date: 05/10/2017
Kindle book details: Kindle Edition, 320 pages
[1] 2345Next
PDFfetch