Network Programmability and Automation
By Edelman, Jason
People who already know Git, Python, data formats and Linux may be annoyed to find them introduced here. But skip forward to the sections which explain Netconf and how to automate network configuration.
Also, people who know Continuous Integration may be annoyed, but there is a valuable discussion of company culture: management buy-in is critical.
- Python programming basics: data types, conditionals, loops, functions, classes, and modules
- Linux fundamentals to provide the foundation you need on your network automation journey
- Data formats and models: JSON, XML, YAML, and YANG for networking
- Jinja templating and its applicability for creating network device configurations
- The role of application programming interfaces (APIs) in network automation
- Source control with Git to manage code changes during the automation process
- How Ansible, Salt, and StackStorm open source automation tools can be used to automate network devices
- Key tools and technologies required for a Continuous Integration (CI) pipeline in network operations
Mining the Social Web
Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
By Russell, Matthew A.; Klassen, Mikhail
Learning Web Design
By Robbins, Jennifer Niederst
Deep Learning Cookbook
Practical Recipes to Get Started Quickly
By Osinga, Douwe
Python for Data Analysis, second edition, Wes McKinney, O’Reilly, 2017
Python is the best language for analyzing large data sets, and Pandas is the best library for doing this. Wes is the creator of Pandas, so he has an intimate knowledge of the subject.
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Who Can You Trust? How Technology Brought Us Together and Why It Might Drive Us Apart,
Rachel Botsman, Penguin, 2017 | First edition: November 2017.
Hundreds of years ago we only trusted people we knew in the village. A hundred years ago brands (think Heintz 57) were invented, and we trusted them. Now we trust the AirBnB host based on her reputation, presumably based on accumulated user reviews (why are they always 4.1 to 4.9?).
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Life 3.0 –
Being Human in the Age of Artificial Intelligence
by Max Tegmark, Knopf, 2017 | First edition.
This is a book about AI, and readable by the layman (might I say gripping). It is about the ‘AI-safety’ research specialty (nowadays you cannot simply research AI, you need to specialize).
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66 Specific Ways to Debug Software and Systems by Diomidis Spinellis, Addison-Wesley, 2017
Programmers will want to read this book, and possibly keep it close by at all times.
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WTF – What’s the Future and Why It’s up to Us,
By Tim O’Reilly, 2017
This book redefines the unicorn concept to be not “a $1 billion startup”, but a rather a technology innovation which is surprising but affects the whole world.
An inspiring book, I will have more to say on this soon.
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The 100-year Life – Living and Working in An Age of Longevity,
Lynda Gratton and Andrew Scott, Bloomsbury Business, 2017
The three phase life (education, employment, retirement) is history now: gone forever. Maybe we will have (learn, work, rest, learn, work, rest…).
Or (learn, work/learn, work/learn, ..). I hope resting time can be in the mix occasionally. This change is due to the gig economy and longer life expectations. This book shows how to rethink your finances, your education, your career and your relationships and create a fulfilling 100-year life.
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