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Gil Zilberfeld11/25/14
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How To Make The Best Decisions

We can get better at it, by making more of them. Learning from mistakes and successes. We can also learn from observing how decisions are made in our different circles, and try to learn how to push a decision through or derail one.

Mike Cottmeyer11/25/14
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The Napoleon Corporal

In my previous post, Replacing Backlog Grooming, I wrote about leveraging a Product Owner (PO) Team instead of the “Scrum” team in Progression Workshops (backlog grooming). It doesn’t matter if you’re doing textbook Scrum or something at scale. Your people still need a shared understanding. If not, you’re going to start seeing a lot of delays and a lot of rework.

Gergo Bogdan11/24/14
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OOP in Python - Part 1

Object Oriented Programming is a programming paradigm which creates “objects” during the phase of programming, by this trying to model the entities from the problem which is need to be solved.

Maneesh Joshi11/24/14
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Top 5 Mobile APM Myths: Myths 3-5

Typically, mobile app developers accept some things they feel they can’t change — ratings, end-to-end visibility, user experience, and so on. However, these can all be avoided and under your control with the right mAPM solution to give you the proper insights to give your users a seamless experience.

Robert Diana11/23/14
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Geek Reading November 19, 2014

These items are the fruits of those ideas, the items I deemed worthy from my daily reading. These items are a combination of tech business news, development news and programming tools and techniques.

Mark Needham11/23/14
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R: Refactoring to dplyr

I’ve been looking back over some of the early code I wrote using R before I knew about the dplyr library and thought it’d be an interesting exercise to refactor some of the snippets.

Maarten Ectors11/23/14
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IoT and Personal Health

I just saw Eric Dishman’s TED session on “Health care should be a team sport“. I love the idea of providing people with chronicle illness the means to be diagnosed and treated remotely and use big data to learn of a large group of patients with similar issues.

John Walter11/23/14
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The Best of the Week (Nov 14): IoT Zone

Make sure you didn't miss anything with this list of the Best of the Week in the IoT Zone (November 7 - November 14). This week includes a look at the WatchKit SDK, the effect of IoT on our lives, and the role of logging in the IoT.

Erich Styger11/22/14
8161 views
1 replies

Engineering Joke of the Week: The Frog

A little engineering humor for your weekend...

Mark Needham11/22/14
6110 views
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R: dplyr - Group by field dynamically

A few months ago I wrote a blog explaining how to dynamically/programatically group a data frame by a field using dplyr but that approach has been deprecated in the latest version. It turns out the ‘group_by_’ function doesn’t want to receive a list of fields so let’s remove the call to list:

Michael Sahota11/21/14
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People over Process

Agile and Lean are a means to an end. Once we are clear what our goals are and our approach is consistent with what we truly value, then we may hope for success. We outline a fundamentally different approach for organizational change: one where valuing people is integral to building lasting success.

Allan Kelly11/21/14
9438 views
3 replies

Does Agile require cultural change?

I sit in Agile conferences and I hear people say “To really become Agile you need culture change.” And I agree with them. But…

Mike Cottmeyer11/21/14
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Replacing Backlog Grooming

Over the last few years, I’ve worked with numerous teams. One thing they all struggle with is backlog grooming. Over the last few years I have evolved my practice of backlog grooming.

Mark Needham11/21/14
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R: Joining multiple data frames

I’ve been looking through the code from Martin Eastwood’s excellent talk ‘Predicting Football Using R‘ and was intrigued by the code which reshaped the data into that expected by glm. I really like dplyr’s pipelining function so I thought I’d try and translate Martin’s code to use that and other dplyr functions.

Rob J Hyndman11/20/14
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Seasonal Periods

The “fre­quency” is the num­ber of obser­va­tions per sea­son. This is the oppo­site of the def­i­n­i­tion of fre­quency in physics, or in Fourier analy­sis, where “period” is the length of the cycle, and “fre­quency” is the inverse of period. When using the ts() func­tion in R, the fol­low­ing choices should be used.