A Primer for Contemporary ‘Machine Learning’ Initiatives
Red Hat’s Ulrich Drepper has a neat write-up at opensource.com on ‘an introduction to machine learning today‘ that both sheds light on the history and past of AI while looking forward to what might come next.
Machine learning and artificial intelligence have changed a lot since the last wave of interest, about 25 years ago.
Machine learning and artificial intelligence (ML/AI) mean different things to different people, but the newest approaches have one thing in common: They are based on the idea that a program’s output should be created mostly automatically from a high-dimensional and possibly huge dataset, with minimal or no intervention or guidance from a human. Open source tools are used in a variety of machine learning and artificial intelligence projects. In this article, I’ll provide an overview of the state of machine learning today.
In the past, AI programs usually were explicitly programmed to perform tasks. In most cases, the machine’s “learning” consisted of adjusting a few parameters, guiding the fixed implementation to add facts to a collection of other facts (a knowledge database), then (efficiently) searching the knowledge database for a solution to a problem, in the form of a path of many small steps from one known solution to the next. In some cases, the database wouldn’t need to or couldn’t be explicitly stored and therefore had to be rebuilt.
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, or even use Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for MakeCode, CircuitPython, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.
Python for Microcontrollers — Python snakes its way on the SparkFun SAMD21 Mini, Hackaday.io, 10k thanks, and Tim’s magazine #Python #Adafruit #CircuitPython @circuitpython @micropython @ThePSF @Adafruit
Get the only spam-free daily newsletter about wearables, running a "maker business", electronic tips and more! Subscribe at AdafruitDaily.com !