Quellen
Ansicht:YouTube-Playlisten (5 URLs)
Informatikpulsar 1 - Vol 1 (32 URLs)
- Google Creative Lab
- googlecreativelab/teachable-machine: Explore how machine learning works, live in the browser. No coding required.
- googlecreativelab/teachable-machine-boilerplate: Boilerplate code for Teachable Machine
- Teachable Machine
- A Neural Network Playground
- How Does Your Phone Know This Is A Dog? - YouTube
- tensorflow/tfjs-core: WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.
- TensorFlow.js | TensorFlow.js | TensorFlow
- Giant Emoji by Jonas Jongejan & Stewart Smith | Experiments with Google
- googlecreativelab/giantemoji
- Enzyklopaedie der Wirtschaftsinformatik
- VirtualNeurons 3
- TensorFlow – Wikipedia
- TensorFlow | TensorFlow
- Stuttgart Neural Network Simulator – Wikipedia
- tensorflow/tensorflow: An Open Source Machine Learning Framework for Everyone
- tensorflow/models: Models and examples built with TensorFlow
- TensorFlow Core | TensorFlow
- Machine Learning Glossary | Google Developers
- Machine Learning Glossary | Google Developers
- TensorFlow Core | TensorFlow
- Page Not Found
- UCI Machine Learning Repository
- Christian Borgelt's Web Pages
- API Documentation | TensorFlow Core r1.14 | TensorFlow
- zefman/Brainwave: A JavaScript neural network learning using genetic algorithms
- Neural Networks in JavaScript with deeplearn.js - RWieruch
- All symbols in TensorFlow 2.0 Preview | TensorFlow Core r1.14 | TensorFlow
- Building a real-time smile detection app with deeplearn.js and the web shape detection API — Part 2: Image Processing
- Künstliche Intelligenz: Kann der Gott der Zukunft ein Computer sein? | ZEIT ONLINE
- Page Not Found
- Machine Learning with Python: Neural Network with Python using Numpy
Informatikpulsar 1 - Vol 2 (37 URLs)
- wie funktioniert das gehirn at DuckDuckGo
- Wie funktioniert das Gehirn? - gesundheitsinformation.de
- Gedächtnis | dasGehirn.info - der Kosmos im Kopf
- Gehirn – Wikipedia
- Nervenzelle – Wikipedia
- Nervensystem – Wikipedia
- Ontogenese – Wikipedia
- Tintenfische – Wikipedia
- Zerebralisation – Wikipedia
- Magnetoenzephalographie – Wikipedia
- Elektroenzephalografie – Wikipedia
- Neuronales Netz – Wikipedia
- Bewusstsein – Wikipedia
- Rezeptor (Biochemie) – Wikipedia
- Vegetatives Nervensystem – Wikipedia
- Plexus (Medizin) – Wikipedia
- Neuron (Begriffsklärung) – Wikipedia
- Neuronentheorie – Wikipedia
- Gliazelle – Wikipedia
- Erregungsleitung – Wikipedia
- Erregungsübertragung – Wikipedia
- Aktionspotential – Wikipedia
- Axon – Wikipedia
- Schwellenpotential – Wikipedia
- Alles-oder-nichts-Gesetz – Wikipedia
- Synapse – Wikipedia
- Neurotransmitter – Wikipedia
- Nerv – Wikipedia
- Neuronale Netze - Eine Einführung - Grundlagen
- Wayback Machine
- Haut – Wikipedia
- Die Hautrezeptoren - Infoquelle
- Grundumsatz – Wikipedia
- Gehirn und Lernen - Das Nervensystem
- Wie funktioniert das Nervensystem? - gesundheitsinformation.de
- Elektrophysiologie – Wikipedia
- Neural backpropagation - Wikipedia
Informatikpulsar 1 - Vol 3 (33 URLs)
- Künstliches neuronales Netz – Wikipedia
- Enzyklopaedie der Wirtschaftsinformatik
- Künstliche neuronale Netze – Aufbau & Funktionsweise – JAAI.de
- Microsoft Word - Folien.doc - OptimierungKNNFolien.pdf
- Künstliches Neuron – Wikipedia
- Künstliche Intelligenz – Wikipedia
- Neuron (Begriffsklärung) – Wikipedia
- Neuron (Software) – Wikipedia
- Computational Neuroscience – Wikipedia
- Machine Learning Glossary | Google Developers
- Machine Learning Glossary | Google Developers
- Neuronale Netze - Eine Einführung - Grundlagen
- Wayback Machine
- Watson (Künstliche Intelligenz) – Wikipedia
- Turing-Test – Wikipedia
- Human Brain Project – Wikipedia
- Maschinelles Lernen – Wikipedia
- Artificial neural network - Wikipedia
- How Deep Neural Networks Work - YouTube
- Neuronale Netze - Programme Lernen [Informatikreferat] - YouTube
- Elektrophysiologie – Wikipedia
- Keen.pdf
- GenetischeAlgorithmen.pdf
- Microsoft Word - Ausarbeitung.doc - GAES.pdf
- ga.pdf
- Christian Borgelt's Web Pages
- Backpropagation - Wikipedia
- Deep learning - Wikipedia
- Backpropagation – Wikipedia
- Evolutionärer Algorithmus – Wikipedia
- Presseinformationen
- The Revolutionary Quantum Computer That May Not Be Quantum at All | WIRED
- Matrizenmultiplikation - Mathebibel.de
Informatikpulsar 2 - Vol 1 (11 URLs)
- Convolutional Neural Networks (CNNs) explained - deeplizard
- neural network backpropagation at DuckDuckGo
- A Step by Step Backpropagation Example – Matt Mazur
- Gradient descent - Wikipedia
- Chain rule - Wikipedia
- Notation for differentiation - Wikipedia
- Track human poses in real-time on Android with TensorFlow Lite
- How to classify butterflies with deep learning in Keras
- Everything you need to know about Neural Networks and Backpropagation — Machine Learning Easy and Fun
- Skymind | A Beginner's Guide to Backpropagation in Neural Networks
- 30 Things I Wish I Knew When I Started Programming - Better Programming - Medium
Informatikpulsar 2 - Vol 2 (9 URLs)
- machine learning - Backpropagate multiple hidden layers - Cross Validated
- machine learning - backpropagation for multiple hidden layers - Cross Validated
- Build a flexible Neural Network with Backpropagation in Python - DEV Community 👩💻👨💻
- Mind: How to Build a Neural Network (Part One)
- Neural Networks Demystified [Part 1: Data and Architecture] - YouTube
- stephencwelch/Neural-Networks-Demystified: Supporting code for short YouTube series Neural Networks Demystified.
- stephencwelch (Stephen)
- mozilla/DeepSpeech: A TensorFlow implementation of Baidu's DeepSpeech architecture
- mozilla/TTS: Deep learning for Text to Speech
Informatikpulsar 3 - Vol 1 (14 URLs)
- 6 Types of Artificial Neural Networks Currently Being Used in ML
- types of artificial neural networks at DuckDuckGo
- a mostly complete chart of neural networks at DuckDuckGo
- Artificial neuron - Wikipedia
- Backpropagation - Wikipedia
- Perceptron - Wikipedia
- Types of artificial neural networks - Wikipedia
- Neural Networks from Scratch with Python Code and Math in Detail— I | by Towards AI Team | Towards AI — Multidisciplinary Science Journal | Medium
- Main Types of Neural Networks and its Applications — Tutorial | Towards AI — Multidisciplinary Science Journal
- 1*cuTSPlTq0a_327iTPJyD-Q.png (PNG Image, 1000 × 1500 pixels) - Scaled (44%)
- 1*8QQDK0U1DCBJ7uFXCO36Mw.png (PNG Image, 1350 × 759 pixels) - Scaled (87%)
- The mostly complete chart of Neural Networks, explained | by Andrew Tch | Towards Data Science
- A Comprehensive Guide to Types of Neural Networks
- Machine Learning | CMU | Carnegie Mellon University
Informatikpulsar 3 - Vol 2 (15 URLs)
- Alles-oder-nichts-Gesetz – Wikipedia
- Alles-oder-nichts-Prinzip – Wikipedia
- MIT Deep Learning and Artificial Intelligence Lectures | Lex Fridman
- Build a flexible Neural Network with Backpropagation in Python - DEV
- List of animals by number of neurons - Wikipedia
- Transistor - Wikipedia
- Die Welt der Künstlichen Intelligenz - Futurium
- Am Anfang war der Automat - Futurium
- To Build Truly Intelligent Machines, Teach Them Cause and Effect
- lexfridman/mit-deep-learning: Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- ITP-NYU - Spring 2016
- Welcome to Mozilla Voice - Mozilla Voice
- Intro to matrix multiplication (video) | Khan Academy
- How many bits of data can a neuron or synapse hold? : askscience
- Action Potential in the Neuron - YouTube