Bayesian inference is a way to get sharper predictions from your data. It’s particularly useful when you don’t have as much data as you would like and want to juice every last bit of predictive strength from it.
Although it is sometimes described with reverence, Bayesian inference isn’t magic or mystical. And even though the math under the hood can get dense, the concepts behind it are completely accessible. In brief, Bayesian inference lets you draw stronger conclusions from your data by folding in what you already know about the answer.
Bayesian inference is based on the ideas of Thomas Bayes, a nonconformist Presbyterian minister in London about 300 years ago. He wrote two books, one on theology, and one on probability. His work included his now famous Bayes Theorem in raw form, which has since been applied to the problem of inference, the technical term for educated guessing. The popularity of Bayes’ ideas was aided immeasurably by another minister, Richard Price. He saw their significance, refined them and published them. It would be more accurate and historically just to call Bayes’ Theorem the Bayes-Price Rule.
plotnine is an implementation of a grammar of graphics in Python, it is based on ggplot2. The grammar allows users to compose plots by explicitly mapping data to the visual objects that make up the plot.
Plotting with a grammar is powerful, it makes custom (and otherwise complex) plots are easy to think about and then create, while the simple plots remain simple.
To find out about all building blocks that you can use to create a plot, check out the documentation. Since plotnine has an API similar to ggplot2, where we lack in coverage theggplot2 documentation may be of some help.
Google announced Kotlin as an official language for Android development. Some famous developer companies, like square, started using kotlin as their production language long before the official announcement was made.
Now one of the most trending questions juggling around the minds of many experts and most beginners is should I learn kotlin or stick to java? Here’s some point should be made based on three stages of a developers like really really beginner, ninja apprentice, totally ninja.
Google has already expressed several times that they don’t have anything against Kotlin, and that they’re not preventing us from using it while the compiler still generates valid bytecode.
But many people is still waiting for an official support, something that could never happen.
While we wait until that moment though, I thought it would be nice to know what the Google Developers Experts for Android think about it.
If you hadn’t heard about it, Google Developers Experts (GDEs) is a program that recognizes outstanding developers the effort to be a reference on the field they are involved in.
I contacted some of these Android Experts (the list is huge!), and I got answers from 17 of them. Thanks a lot for being so nice and taking your time to answer!
I’ve just asked them to tell us a bit about them, and what they think about Kotlin. The answers are obviously unmodified, so you will find voices for and against (or not so for) the language.
I really hope this helps you form an idea of how Kotlin is being a game changer, and that, at least, is a language to take into account if you are an Android developer.
Without further delay, here it is the opinion of our GDEs in no particular order:…
Chalice is a serverless microframework that makes it simple for you to use AWS Lambda and Amazon API Gateway to build serverless apps. We’ve improved Chalice based on community feedback from GitHub, and we’re eager for you to take our latest version for a spin. Hopefully, you’ll find Chalice a fast and effective way to build serverless apps.
To help you get started with Chalice, here’s a quick five-step review:
Step 1: Install Chalice
Step 2: Configure credentials
Step 3: Create a project
Step 4: Deploy your API
Step 5: You’re done launching a simple API. Consider adding something to your app!
Let’s dig in.
“Welcome to engineering management. It’s fun, it’s exhausting, it’s rewarding — but most importantly it’s new! What worked for you before won’t work now. You’ll have to acquire a new set of skills, and shed some bad habits in the process. Here is a short guide to get you started…”
A basic week-end project: Go based dashboard for Google Analytics real time API
“To celebrate my sub-30 minute finish on the manitou springs incline, I figured I’d drop some python and pandas knowledge while analyzing the data using beautifulsoup, pandas, python dateutil, python googlemaps, python geopy and the standard library.
I try to look at things in a non-trivial way and reflective of actual problems you encounter analyzing real world data. The data file is here https://gist.github.com/jrjames83/4de9d124e5f43a61be9cb2a… come code along!”
As part of the normal cycle of things, our most recent boom in enterprise technology development has slowed, which always leaves the industry breathless about whatever’s left that’s actually new. Witness, for example, the current mania over AI and machine learning.
I’ve had my fill of AI-washing, so the most interesting new area to me today is serverless computing, which hit the radar a couple of years ago when Amazon introduced AWS Lambda. The basic idea is that, finally, developers can build without worrying about physical or virtual servers or even containers. Instead, devs can simply assemble services from small building blocks of code called functions, and all that messy infrastructure stuff under the hood takes care of itself.