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Showing posts from July, 2021

It Was About Time To Find A Shared Vision Of Perl

  The Perl Foundation (TPF) is looking pretty active lately, undertaking a number of initiatives which aim to advance Perl's ecosystem further. The start came with  "Coding in Perl? What support do you need?" , a survey into what help and guidance Perl beginners would find useful, which we reported in  "New To Perl? What Do You Need? The Results" . Among other findings, it was revealed that beginners would like a standardized way of doing things along the lines of a framework, they crave the security and agility that an IDE provides, and that, when they look for help, their preference is first books and then online courses and videos, relegating real-time chat and one-to-one contact at the final places.   full article on

Python3 Course For InfoSec Pros

  A free course by InfoSecAddicts, to teach Python from an Infosec Pro's perspective. It aims to cover the minimum Python that you can apply in the field to accomplish day-to-day Infosec tasks. full article on

Spring GraphQL Milestone One

  A new library aims to unify all the previous approaches of accessing GraphQL from Spring. The Spring GraphQL project, which has reached its initial milestone towards a 1.0 release, integrates GraphQL, Java and Spring and was developed as a collaboration between both teams. Until now the way you accessed GraphQL from Spring was through the standard GraphQL Java Spring project which at the minimum would expose a /graphql endpoint (something that as well as the transport agnostic, was missing from the original GraphQL Java library) in order to accept the GraphQL payloads over HTTP; or the newest counterpart, that of the Netflix DGS Framework (Domain Graph Service). full article on

GAN Theft Auto - The Neural Network Is The Game

  GAN Theft Auto is a fork of the Nvidia's GameGAN emulating dynamic game environments neural network but applied to Grand Theft Auto. A couple of researchers replicated a "simple" scene of Grand Theft Auto;a car driving around a highway.The difference is that the car as well as the surrounding environment obeys to rules not pre-written by a game engine but the neural network itself.   full article on

The Linux Upskill Challenge

  A compact and previously paid course is now free and open source. It teaches everything someone needs in order to transition to Linux. The range of subjects covered includes a treat for everyone;from setting up your own lab on a VPS and accessing it, to installing software, exploring the file structure, working with the CLI and its commands, to more advanced subjects like scripting on bash   full article on

Introduction to Machine Learning with Scikit-Learn

  A free course on the fundamentals of Machine Learning with Python, taught by Kevin Markham founder of Data School, helps you ease your way into ML and scikit-learn, one of the best-known libraries for this purpose. Python certainly is the most popular language of doing ML, mainly due to the number of relevant libraries available. scikit-learn is one of tho top Machine Learning libraries alongside PyTorch, NumPy, SciPy, TensorFlow and Theano. Additionally, scikit-learn is one of the easiest to learn as such perfect for beginning one's ML journey. That doesn't mean that it lacks functionality though; it is perfectly capable of pulling off many ML tasks such as classification, clustering, pre-processing, regression, etc. full article on

Learn Python with HackInScience

  HackInScience is a code challenge site that is mostly oriented towards learning than competing with others for a top ranking despite the presence of a Leaderboard. It's a playground of fun Python exercises, each with a user-friendly correction bot. In order to showcase this, let's look at a simple exercise,"Characters counting" which requires writing code to  "Print the number of characters in the given paragraph". full article on