Author: Joyce Xu Before I started my most recent job at ThinkTopic, the concepts of “functional programming” and “machine learning” belonged to two different worlds entirely. One was a programming paradigm surging in popularity as the world turned towards simplicity, composability, and immutability to maintain complex scaling applications; the other was a tool to teach computers to autocomplete doodles and make […]
Author: Favio Vázquez Hi everyone. This blog post comes from 3 post I did recently at LinkedIn. Here they are Part 1, Part 2, and Part 3. This is a hard question to answer. Hang with me in this one (and this is not the final answer about the universe, existence and everything). This is one […]
1) Francesco Pugliese – Co-Founder Deep Learning Italia | Ricercato ISTAT “Introduzione divulgativa alle Reti Neurali e al Deep Learning”. Abstract: Descrizione introduttiva del modello del neurone artificiale e confronto con il neurone biologico, la storia delle reti neurali e come si è arrivati oggi al Deep Learning, detrattori vs sostenitori delle reti neurali e […]
Cristiano De Nobili – Fisico “Convolutional autoencoders features visualization” Le reti CNN formano delle rappresentazioni a ogni livello, le feature maps, e i livelli più lontani dal livello di input contengono features via via sempre più complesse, che catturano caratteristiche che descrivono grandi porzioni dell’immagine di input. In questo talk faremo vedere una tipica […]
Daniele D’Armiento – Physicist presso Samsung “Introduzione al deep learning ed alla piattaforma Deep Learning Italia” Abstract: Illustrazione della community Deep Learning Italia e degli strumenti oggi sviluppati e a disposizione della community. Introduzione alle features del sito www.deeplearningitalia.com: i tutorials, il question & answer, le references, gli sviluppi futuri
Author Joyce Xu With the rise of autonomous vehicles, smart video surveillance, facial detection and various people counting applications, fast and accurate object detection systems are rising in demand. These systems involve not only recognizing and classifying every object in an image, but localizing each one by drawing the appropriate bounding box around […]
Author: Joyce Xu Over the past few years, much of the progress in deep learning for computer vision can be boiled down to just a handful of neural network architectures. Setting aside all the math, the code, and the implementation details, I wanted to explore one simple question: how and why do these […]
Author: Nathan Hubens Linkedind: https://www.linkedin.com/in/nathan-hubens Autoencoders (AE) are neural networks that aims to copy their inputs to their outputs. They work by compressing the input into a latent-spacerepresentation, and then reconstructing the output from this representation. This kind of network is composed of two parts : Encoder: This is the part of the network that compresses the input into […]
Author: Chintan Trivedi Comparison of Cristiano Ronaldo’s face, with the left one from FIFA 18 and the right one generated by a Deep Neural Network. Game Studios spend millions of dollars and thousands of development hours designing game graphics in trying to make them look as close to reality as possible. While the […]
Author: Chintan Trivedi Linkedin: https://www.linkedin.com/in/chintan-trivedi-78665774/ A.I. bots in gaming are usually built by hand-coding a bunch of rules that impart game-intelligence. For the most part, this approach does a fairly good job of making the bot imitate human-like behavior. However, for most games it is still easy to tell apart a bot from an actual human […]