Class´Code v2

Council of Europe Language Policy Portal Languages are a fundamental aspect of people’s lives and the democratic functioning of society. In response to the needs identified in or by its member states, the Council of Europe has been working over the past few decades to compile a set of resources made available to education authorities and professionals and benefiting all Europe’s citizens (see milestones). Some of the end products have been widely distributed beyond Europe. The objectives of the Language policy Programme form part of the broader role and goals of the Council of Europe (in the context of the European Cultural Convention), concerning in particular the rights of individuals, social inclusion and cohesion, intercultural understanding and equal access to quality education. Language learners/users lie at the heart of the work of the Language Policy Programme.

What is the Difference Between Machine Code and Bytecode - Pediaa.Com The main difference between machine code and bytecode is that the machine code is a set of instructions in machine language or binary that can be directly executed by the CPU while the bytecode is an intermediate code generated from compiling a source code which can be executed by a virtual machine. A computer program is a collection of instructions that perform a specific task. A special software such as compilers or interpreters transforms the program into a machine-readable machine code.

Building Brains on the Edge: Running TensorFlow Lite models on microcontrollers by Alasdair Allan @aallan @hacksterio @tensorflow #tensorflow #tensorflowlite #tinyML Building Brains on the Edge: Running TensorFlow Lite models on microcontrollers by Alasdair Allan at the Hackster Blog. Building on the initial demo built by the TensorFlow team at Google, Adafruit has invested a lot of time over the last month into iterating the tooling around the speech demo to make it easy to build and deploy models.They’ve also put together a TensorFlow Lite for Micro-controllers Kit and accompanying the kit is a quick start guide and guide on how to train new voice models on your desktop with Docker. Read more. Related: MACHINE LEARNING MONDAY! Designing the Machine Learning board on the EDGE… BRAINCRAFT!

Neuromyth 1 The brain is only plastic for certain kinds of information during specific ‘critical periods’-thereby the first three years of a child are decisive for later development and success in life. The concept of critical periods states that there are certain periods during early life when the brain’s capacity for adjustment in response to experience is substantially greater than it is in adulthood. This concept originated from observations by some of the pioneers in the study of animal behaviour. For example, Konrad Lorenz examined a dramatic example of a critical period: imprinting in birds. Newly hatched birds will become indelibly attached, or imprinted, to almost any prominent moving object in their environment, normally their mother.

Useful Resources for Developers A list of student collated resources deemed to be useful for every developer and catergorised. Andrei has a hand picked list of his favourite resources which you can find here. Table of Contents Build a Teachable Machine with Coral's USB Accelerator Coral’s new USB Accelerator lets you to build AI capabilities into any Raspberry Pi project. The accelerator is built around Google’s Edge TPU chip, an ASIC that greatly speeds up neural network performance on-device. In this tutorial we’re going to build a Teachable Machine. This project was designed by Google’s Mike Tyka. Centre for Educational Neuroscience Teachers and parents have a great enthusiasm for the brain sciences and the light they can shed on children’s and adults’ learning in educational environments. We share that enthusiasm at the CEN. However, we also believe that sometimes this enthusiasm can lead to educators too readily accepting teaching practices, ideas, or techniques that do not actually have a scientific basis in neuroscience – or which reflect some basis in neuroscience but have not been rigorously tested within an educational context. This phenomenon has been labelled the spread of ‘neuromyths’ – mistaken ideas about the brain – and it has been the topic of discussion by researchers within neuroscience (e.g., articles by Goswami and Howard-Jones, see this report from the Royal Society).

New Year's Resolution: Learn to Code A year ago I didn't know how to code. I had a journalism degree and had made some graphics, but I would have been hard-pressed to explain the difference between Ruby and JavaScript, and I was pretty happy when I got the YouTube video to embed correctly. I considered myself pretty technical but generally avoided the command line. When I did start learning, I was amazed by how much was out there: introductory videos, explanatory blog posts, tips and tricks and step-by-step guides. If you're a journalist who wants to make a news app or a student interested in learning to code, you have plenty of paths to choose from. To get coding quickly, nothing beats having a project – and a deadline.

A Neural Network Playground Data Which dataset do you want to use? Features Which properties do you want to feed in? Neuromyth Busters - [Everyday] Psychophilosophy Science and technology revolutionize our lives, but memory, tradition, and myth frame our response. — Arthur M. Schlesinger After watching a good movie like Dr. Strange, or a terrible movie like Lucy, you may come to believe the powers of the mind are far greater than we think.

47 of The Best Places to Learn to Code For Free Please note: all information, topics taught, etc., have been taken at time of updating (July 2018) and are definitely subject to change. Thanks! Classpert is a search engine that helps you find and compare online courses in computer science, data science, business, and more. With over 140,000 free and paid courses from more than 30 course providers, you’ll be spoilt for choice. You can even watch course previews and compare syllabuses side-by-side to find the best course for you.

How to install TensorFlow on Raspberry Pi Google TensorFlow 1.9 officially supports the Raspberry Pi, making it possible to quickly install TensorFlow and start learning AI techniques with a Raspberry Pi. Back in The MagPi issue 71 we noted that it was getting easier to install TensorFlow on a Raspberry Pi. This latest news makes installing TensorFlow 1.9 as simple as using pip. Pete Warden, a Software Engineer at Google writes Thanks to a collaboration with the Raspberry Pi Foundation, we’re now happy to say that the latest 1.9 release of TensorFlow can be installed from pre-built binaries using Python’s pip package system! Paul Ford: What Is Code? A computer is a clock with benefits. They all work the same, doing second-grade math, one step at a time: Tick, take a number and put it in box one. Tick, take another number, put it in box two. Tick, operate (an operation might be addition or subtraction) on those two numbers and put the resulting number in box one. Tick, check if the result is zero, and if it is, go to some other box and follow a new set of instructions. You, using a pen and paper, can do anything a computer can; you just can’t do those things billions of times per second.