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Designing Bots: Creating Conversational Experiences

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

UX Strategy: How to Devise Innovative Digital Products that People Want

User experience (UX) strategy requires a careful blend of business strategy and UX design, but until now, there hasn’t been an easy-to-apply framework for executing it. This hands-on guide introduces lightweight strategy tools and techniques to help you and your team craft innovative multi-device products that people want to use.Whether you’re an entrepreneur, UX/UI designer, product manager, or part of an intrapreneurial team, this book teaches simple-to-advanced strategies that you can use in your work right away. Along with business cases, historical context, and real-world examples throughout, you’ll also gain different perspectives on the subject through interviews with top strategists.
  • Define and validate your target users through provisional personas and customer discovery techniques
  • Conduct competitive research and analysis to explore a crowded marketplace or an opportunity to create unique value
  • Focus your team on the primary utility and business model of your product by running structured experiments using prototypes
  • Devise UX funnels that increase customer engagement by mapping desired user actions to meaningful metrics
Author: Jaime Levy
Published by: O'Reilly Media | Publication date: 05/20/2015
Kindle book details: Kindle Edition, 312 pages

SQL Cookbook: Query Solutions and Techniques for Database Developers (Cookbooks (O'Reilly))

You know the rudiments of the SQL query language, yet you feel you aren't taking full advantage of SQL's expressive power. You'd like to learn how to do more work with SQL inside the database before pushing data across the network to your applications. You'd like to take your SQL skills to the next level.Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT columns FROM table WHERE conditions. But there is so much more you can do with the language. In the SQL Cookbook, experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:
  • Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing out
  • Powerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES function
  • Pivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result set
  • Bucketization, and why you should never use that term in Brooklyn.
  • How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniques
  • The technique of walking a string, which allows you to use SQL to parse through the characters, words, or delimited elements of a string
Written in O'Reilly's popular Problem/Solution/Discussion style, the SQL Cookbook is sure to please. Anthony's credo is: "When it comes down to it, we all go to work, we all have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days." The SQL Cookbook moves quickly from problem to solution, saving you time each step of the way.
Published by: O'Reilly Media | Publication date: 12/16/2005
Kindle book details: Kindle Edition, 634 pages

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

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

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field.Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.
Published by: O'Reilly Media | Publication date: 05/25/2017
Kindle book details: Kindle Edition, 298 pages

High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark

Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources.Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing.With this book, you’ll explore:
  • How Spark SQL’s new interfaces improve performance over SQL’s RDD data structure
  • The choice between data joins in Core Spark and Spark SQL
  • Techniques for getting the most out of standard RDD transformations
  • How to work around performance issues in Spark’s key/value pair paradigm
  • Writing high-performance Spark code without Scala or the JVM
  • How to test for functionality and performance when applying suggested improvements
  • Using Spark MLlib and Spark ML machine learning libraries
  • Spark’s Streaming components and external community packages
Published by: O'Reilly Media | Publication date: 05/25/2017
Kindle book details: Kindle Edition, 358 pages

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

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, 336 pages

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
  • Peer under the hood of the systems you already use, and learn how to use and operate them more effectively
  • Make informed decisions by identifying the strengths and weaknesses of different tools
  • Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
  • Understand the distributed systems research upon which modern databases are built
  • Peek behind the scenes of major online services, and learn from their architectures
Published by: O'Reilly Media | Publication date: 03/16/2017
Kindle book details: Kindle Edition, 614 pages

Practical Statistics for Data Scientists: 50 Essential Concepts

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

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

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, 566 pages
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