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Mastering Bitcoin: Programming the Open Blockchain

https://www.amazon.com/Mastering-Bitcoin-Programming-Open-Bl...
Join the technological revolution that’s taking the financial world by storm. Mastering Bitcoin is your guide through the seemingly complex world of bitcoin, providing the knowledge you need to participate in the internet of money. Whether you’re building the next killer app, investing in a startup, or simply curious about the technology, this revised and expanded second edition provides essential detail to get you started.Bitcoin, the first successful decentralized digital currency, is still in its early stages and yet it’s already spawned a multi-billion-dollar global economy open to anyone with the knowledge and passion to participate. Mastering Bitcoin provides the knowledge. You simply supply the passion.The second edition includes:
  • A broad introduction of bitcoin and its underlying blockchain—ideal for non-technical users, investors, and business executives
  • An explanation of the technical foundations of bitcoin and cryptographic currencies for developers, engineers, and software and systems architects
  • Details of the bitcoin decentralized network, peer-to-peer architecture, transaction lifecycle, and security principles
  • New developments such as Segregated Witness, Payment Channels, and Lightning Network
  • A deep dive into blockchain applications, including how to combine the building blocks offered by this platform into higher-level applications
  • User stories, analogies, examples, and code snippets illustrating key technical concepts
Published by: O'Reilly Media | Publication date: 06/12/2017
Kindle book details: Kindle Edition, 410 pages

Introducing Python: Modern Computing in Simple Packages

https://www.amazon.com/Introducing-Python-Modern-Computing-P...
Easy to understand and fun to read, Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.
  • Learn simple data types, and basic math and text operations
  • Use data-wrangling techniques with Python’s built-in data structures
  • Explore Python code structure, including the use of functions
  • Write large programs in Python, with modules and packages
  • Dive into objects, classes, and other object-oriented features
  • Examine storage from flat files to relational databases and NoSQL
  • Use Python to build web clients, servers, APIs, and services
  • Manage system tasks such as programs, processes, and threads
  • Understand the basics of concurrency and network programming
Published by: O'Reilly Media | Publication date: 11/11/2014
Kindle book details: Kindle Edition, 484 pages

Python Crash Course: A Hands-On, Project-Based Introduction to Programming

https://www.amazon.com/Python-Crash-Course-Hands-Project-Bas...
Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course you’ll learn how to:–Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal–Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses–Work with data to generate interactive visualizations–Create and customize Web apps and deploy them safely online–Deal with mistakes and errors so you can solve your own programming problemsIf you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!Uses Python 2 and 3
Author: Eric Matthes
Published by: No Starch Press | Publication date: 11/01/2015
Kindle book details: Kindle Edition, 562 pages

Stonewalled: My Fight for Truth Against the Forces of Obstruction, Intimidation, and Harassment in Obama's Washington

https://www.amazon.com/Stonewalled-Obstruction-Intimidation-...
Seasoned CBS reporter Sharyl Attkisson reveals how she has been electronically surveilled while digging deep into the Obama Administration and its scandals, and offers an incisive critique of her industry and the shrinking role of investigative journalism in today’s media.Americans are at the mercy of powerful figures in business and government who are virtually unaccountable. The Obama Administration in particular has broken new ground in its monitoring of journalists, intimidation and harassment of opposition groups, and surveillance of private citizens.Sharyl Attkisson has been a journalist for more than thirty years. During that time she has exposed scandals and covered controversies under both Republican and Democratic administrations. She has also seen the opponents of transparency go to ever greater lengths to discourage and obstruct legitimate reporting.Attkisson herself has been subjected to “opposition research” efforts and spin campaigns. These tactics increased their intensity as she relentlessly pursued stories that the Obama Administration dismissed. Stonewalled is the story of how her news reports were met with a barrage of PR warfare tactics, including online criticism, as well as emails and phone calls up the network chain of command in an effort to intimidate and discourage the next story. In Stonewalled, Attkisson recounts her personal tale, setting it against the larger story of the decline of investigative journalism and unbiased truth telling in America today.
Published by: Harper | Publication date: 11/04/2014
Kindle book details: Kindle Edition, 425 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, 318 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, 574 pages

Lean Enterprise: How High Performance Organizations Innovate at Scale (Lean (O'Reilly))

https://www.amazon.com/Lean-Enterprise-Performance-Organizat...
How well does your organization respond to changing market conditions, customer needs, and emerging technologies when building software-based products? This practical guide presents Lean and Agile principles and patterns to help you move fast at scale—and demonstrates why and how to apply these methodologies throughout your organization, rather than with just one department or team.Through case studies, you’ll learn how successful enterprises have rethought everything from governance and financial management to systems architecture and organizational culture in the pursuit of radically improved performance. Adopting Lean will take time and commitment, but it’s vital for harnessing the cultural and technical forces that are accelerating the rate of innovation.
  • Discover how Lean focuses on people and teamwork at every level, in contrast to traditional management practices
  • Approach problem-solving experimentally, by exploring solutions, testing assumptions, and getting feedback from real users
  • Lead and manage large-scale programs in a way that empowers employees, increases the speed and quality of delivery, and lowers costs
  • Learn how to implement ideas from the DevOps and Lean Startup movements even in complex, regulated environments
Published by: O'Reilly Media | Publication date: 12/04/2014
Kindle book details: Kindle Edition, 352 pages

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

https://www.amazon.com/Data-Science-Transform-Visualize-Mode...
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.You’ll learn how to:
  • Wrangle—transform your datasets into a form convenient for analysis
  • Program—learn powerful R tools for solving data problems with greater clarity and ease
  • Explore—examine your data, generate hypotheses, and quickly test them
  • Model—provide a low-dimensional summary that captures true "signals" in your dataset
  • Communicate—learn R Markdown for integrating prose, code, and results
Published by: O'Reilly Media | Publication date: 12/12/2016
Kindle book details: Kindle Edition, 522 pages

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

https://www.amazon.com/Designing-Data-Intensive-Applications...
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, 624 pages

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

https://www.amazon.com/Data-Science-Business-Data-Analytic-T...
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.
  • Understand how data science fits in your organization—and how you can use it for competitive advantage
  • Treat data as a business asset that requires careful investment if you’re to gain real value
  • Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way
  • Learn general concepts for actually extracting knowledge from data
  • Apply data science principles when interviewing data science job candidates
Published by: O'Reilly Media | Publication date: 07/27/2013
Kindle book details: Kindle Edition, 414 pages
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