company:neural networks

How to Understand Machine Learning with simple Code Examples
▻https://hackernoon.com/how-to-understand-machine-learning-with-simple-code-examples-a0508dae212

https://cdn-images-1.medium.com/max/1024/1*rgr_UVVil3yW3ByxyX00ew.png

Understanding machine learning using simple code examples.“Machine Learning, Artificial Intelligence, Deep Learning, Data Science, Neural Networks”You must’ve surely read somewhere about how these things are gonna take away future jobs, overthrow us as dominant species on earth and how we’d have to find Arnold Schwarzenegger and John Connor to save humanity.With current hype, there is no surprise you might have.But, what is Machine Learning and what is Artificial Intelligence?Machine learning is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.And what is Neural Network?Artificial neural (...)

#deep-learning #artificial-intelligence #neural-networks #machine-learning #javascript

Understanding How Artificial Intelligence Can Make #blockchain Safer and Smarter
▻https://hackernoon.com/understanding-how-artificial-intelligence-can-make-blockchain-safer-and-

https://cdn-images-1.medium.com/max/1024/1*XfEq_cHD7Z2Y5V3RLydOjQ.png

In the AI field, you can build smart Machine Learning algorithms or impressive Neural Networks, but this powerful technology could be trustable or could generate intelligent responses based on the data you use when you train it.As I wrote in my article: Understanding The Gold Rush of Scalable and Validated Data powered by Blockchain and Decentralized AI for Hackernoon:The best results in the AI field are in closed and well-defined ecosystems, such as video games, where AI algorithms have beaten every world champions, even in DOTA 2, considered one of the most complex video game in the industry… …In open environments like social media or big data, AI’s algorithms have performed less, or sometimes AI’s results are dangerously wrong.Wait but why?In scripted environments like video games, you (...)

#smart-contracts #artificial-intelligence #blockchain-ai

The Perceptron
▻http://constantvzw.org/site/The-Perceptron.html

In machine learning, the perceptron is an #Algorithm for supervised learning of binary classifiers. A binary classifier is a model which can decide whether an input belongs to some specific class. Neural Networks work the same way as the perceptron. Perceptron is a single layer neural network and a multi-layer perceptron is called Neural Networks. During this session we will perform the Perceptron physically as a game. Afterwards, we will look at the code. For those wishing to experiment (...)

#Algolit

/ #Workshop, #Netnative_literature, Algorithm

How I become Blockchain developer and Smart contract hacker
▻https://hackernoon.com/how-i-become-blockchain-developer-and-smart-contract-hacker-14f7608e743a

https://cdn-images-1.medium.com/max/1024/1*ND7KaK413kFB8D-kPUZpPQ.jpeg

Half a year to become middle smart contract hackerMy first failFor about two years i were a freelance Android developer and studied Machine Learning and Neural Networks. At the end of 2017 i decided to become Data Scientist or Blockchain Developer and put my CV on some hiring services and continued working as Android developer. At the same time i started learning blockchain and trading, so we created telegram channel with my friend where we shared review of blockchain projects with some score and predict(like a lot of rating agencies now). I had a goal to finish my Android project at the end of December and to start searching some Blockchain related work at the beginning of 2018. However, at the first week of December i got a call from Sberbank Technologies for an interview and agreed. (...)

Narrative perspective of Neural Networks #8
▻http://constantvzw.org/site/Narrative-perspective-of-Neural-Networks-8.html

Algolit explores neural networks to see how their process can be made legible, visible, understandable. We follow up on the Deep Learning and Natural Language Processing course from Stanford University, by Richard Socher (►https://cs224d.stanford.edu/syllabus.html). Please make sure you watch the first five video’s of the course. Impressions and algoliterary experiments are shared throughout the day. Find notes of previous ones: ▻http://pad.constantvzw.org/public_pad/neural_networks_7 (...)

#Algolit / #Workshop, #Netnative_literature, #Algorithm

Narrative perspective of Neural Networks #7
▻http://constantvzw.org/site/Narrative-perspective-of-Neural-Networks-7.html

Algolit explores neural networks to see how their process can be made legible, visible, understandable. We follow up on the Deep Learning and Natural Language Processing course from Stanford University, by Richard Socher (►https://cs224d.stanford.edu/syllabus.html). Please make sure you watch the first five video’s of the course. Impressions and algoliterary experiments are shared throughout the day. Find notes of previous ones: ▻http://pad.constantvzw.org/public_pad/neural_networks_6 (...)

#Algolit / #Workshop, #Netnative_literature, #Algorithm

ConvNetJS – Deep Learning in your browser

ConvNetJS is a Javascript library for training Deep Learning models (mainly Neural Networks) entirely in your browser. Open a tab and you’re training. No software requirements, no compilers, no installations, no GPUs, no sweat.

ConvNetJS is a Javascript implementation of Neural networks, together with nice browser-based demos. It currently supports:

Common Neural Network modules (fully connected layers, non-linearities)
Classification (SVM/Softmax) and Regression (L2) cost functions
A MagicNet class for fully automatic neural network learning (automatic hyperparameter search and cross-validatations)
Ability to specify and train Convolutional Networks that process images
An experimental Reinforcement Learning module, based on Deep Q Learning

http://cs.stanford.edu/people/karpathy/convnetjs/cifar10.jpeg

via @oncletom et @ismael_hery

ping @robin

#inteligence_artificielle #machine_learning #réseaux_de_neurones #javascript