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Learn-It-All Mindset Beats the Know-It-All Mindset: Exposing the trial and error process to all is essential.

Different tests of creation of JSON as well as the different JSON-SCHEMA which are attached to them.Īt the end of this “fishing” session, you must, without shame, show your catch as ridiculous as it is and I can draw 2 conclusions from this experience.

#Www anaconda con downloads how to#

How to Integrate User-Centered Design Principles Into Your Day-to-Day Development Work “by Westley Knight.

Concepts extracted from reading “UX for Developers.

A quick exporation of Pippin Williamson’s WP plugin.

Some posts may show up about these subjects in the future. Spearheads of the magic trio: AI, Deep Learning, Machine Learning.

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The Anaconda install was also the opportunity to dig into various librairies such as Tensorflow, Keras (multifunction), NTLK (language), OpenCV (images) and many others.

The opportunity to modestly make some Python & install and explore Anaconda for testing purposes in JSON-schema.

I was bound to ramble into random exploratory directions that made me discover the followings: ** The guy I am working with is called Leo. Since when you use JSON content, you quickly need to make sure that the content as well as the structure will remain perennial. Suddenly, I got interested again in the JSON-Schema, discovered with Postman. FAQs, Changelogs, Quotes, TODOs, Shopping list items… etc. This one could be used to display any content in hierarchical list e.g. It was basically to build a multifunction JSON structure. * “beau comme la rencontre fortuite sur une table de dissection d’une machine à coudre et d’un parapluie.” One more thing, this time again, the content produced is so anarchic that it is almost poetic, beautiful in a sense “as beautiful as the chance encounter of a sewing machine and an umbrella on an operating table” *. You can find the files in my github account More on Except when I decide to wrap the whole stuff with a minimum of work and publish it to keep track of it. Historically, this is also what awaits us all, sink into oblivion.

Normally, these “explorations” are forgotten as quickly as they appeared. So, this post is a living proof of this “Constant curiosity melted with pragmatism” even though it looks at first sight as a discordant mixture of successful and abandoned attempts.

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Anaconda DistributionĪnaconda Distribution is the easiest way to perform Python/R data science and machine learning on Linux, Windows, and Mac OS X.What’s make a good P.O? A constant curiosity melted with pragmatism, tinged with avidity for success (the Trump most revered value). Jupyter Notebooks are an increasingly popular system that combine your code, descriptive text, output, images and interactive interfaces into a single notebook file that is edited, viewed and used in a web browser.

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You can use it to find the packages you want, install them in an environment, run the packages and update them, all inside Navigator. Navigator is an easy, point-and-click way to work with packages and environments without needing to type conda commands in a terminal window. The command line program conda is both a package manager and an environment manager, to help data scientists ensure that each version of each package has all the dependencies it requires and works correctly. It can search for packages on Anaconda Cloud or in a local Anaconda Repository. Official OverviewĪnaconda Navigator is a desktop graphical user interface included in Anaconda that allows you to launch applications and easily manage conda packages, environments and channels without the need to use command line commands. Yes, Anaconda Navigator is safe to download and install on Windows 11, 10.