Mario Martin

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MIT Deep Learning Book (beautiful and flawless PDF version)

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville.<p>If this repository helps you in …

Machine Learning From Scratch

About<p>Python implementations of some of the fundamental Machine Learning models and algorithms from scratch.<p>The purpose of this project is not to …

Machine Learning

Caption this, with TensorFlow

<i>How to build and train an image caption generator using a TensorFlow notebook.</i>In this article, we walk through an intermediate-level tutorial on how …

Deep Learning

[1703.07950] Failures of Gradient-Based Deep Learning

Computer Science > Learning<p>Title: Failures of Gradient-Based Deep Learning<p>Abstract: In recent years, Deep Learning has become the go-to solution for …

Deep Learning AI Limits | Deep Learning Algorithms

Artificial intelligence has reached peak hype. News outlets report that companies have replaced workers with IBM Watson and algorithms are beating …

Machine Learning

Quantum consciousness

<b>Piero Scaruffi</b><p>Piero Scaruffi takes the view that the more we come to know about the brain, the less easy it becomes to explain consciousness in terms …

Consciousness

So you built a Machine Learning model?

You have been working on a Machine Learning project. You collected data from various sources, built your model and got some preliminary results. You …

How DeepMind’s Memory Trick Helps AI Learn Faster - MIT Technology Review

Intelligent machines have humans in their sights. Deep-learning machines already have superhuman skills when it comes to tasks such as face …

Why Google DeepMind Just One-Upped Human Memory

Over time, the more important memories are cemented while the less important bits of information get overwritten.<p>By on<p>The revolution will not be …

Preamble

This repository contains the lecture slides and course description for the Deep Natural Language Processing course offered in Hilary Term 2017 at the …

A Visual Guide To Statistics

A Brown University student creates math lessons for the more visually inclined among us.<p>Statisticians are one of the fastest growing jobs in the country–and for good reason. “As data becomes more and more a part of people’s lives, statistics is becoming more a part of people’s lives,” says Daniel …

Naked Tensor

This is a bare bones example of <i>TensorFlow</i>, a machine learning package published by Google. You will not find a simpler introduction to it.<p>In each …

Ideas on interpreting machine learning

<i>Mix-and-match approaches for visualizing data and interpreting machine learning models and results.</i>You’ve probably heard by now that machine learning …

Machine Learning

How to do Modern Face Recognition with Deep Learning

This post is by Adam Geitgey, Machine Learning Consultant You canThe post How to do Modern Face Recognition with Deep Learning appeared first on …

Deep Learning

How Transfer Learning Really Works

Introduction to image style transfer using deep learning<p>One of the most interesting discussions today around within machine learning is how it might …

Astronomers Deploy AI to Unravel the Mysteries of the Universe

Author: Sarah Scoles. Sarah Scoles Science<p>Date of Publication: 03.06.17.<p>Time of Publication: 7:00 am. 7:00 am<p>Astronomer Kevin Schawinski has spent …

HyperGAN 0.9

A composable GAN API and CLI. Built for developers, researchers, and artists.<p>HyperGAN is currently in open beta.<p><i>Logos generated with</i> …

It is Not Only Deep Learning That Requires Rethinking Generalization

<b>TL;DR</b>, it is not only DNNs that can fit random labels under a setting where correct labels can be fitted with small generalization errors.<p>The recent …

Deep Learning Project Workflow

This document attempts to summarize Andrew Ng's recommended machine learning workflow from his "Nuts and Bolts of Applying Deep Learning" talk at …

Machine Learning

Taxonomy of Methods for Deep Meta Learning

Let’s talk about Meta-Learning because this is one confusing topic. I wrote a previous post about Deconstructing Meta-Learning which explored …

Computer conquers poker using GTX 1080 video card | Ars Technica

Unlike chess and go, poker players don't have full knowledge of the game state.<p>At the end of January, Carnegie Mellon computer scientists achieved a …

Artificial Intelligence

A Groundbreaking New Discovery Explains How the Brain Creates Consciousness

Nobody yet understands how a collection of mushy cells in the brain gives rise to the brilliance of consciousness seen in higher-order animals, …

The Brain

Why Meta-learning is Crucial for Further Advances of Artificial Intelligence?

This article is extended version of the presentation I gave at General AI Challenge kick off meetup organized by GoodAI and MLMU.<p>First of all, I have …

Kalman filter: Intuition and discrete case derivation

Introduction<p>In this post, we will go over derivation of a discrete Kalman filter. We will first set up equations of a system governed by discrete …

Recent Claims Invalid: Emergent Gravity Might Deliver A Universe Without Dark Matter

Gravity is one of the four fundamental forces of nature, which means it’s not derived from anything else – it just is. At least, that’s according to our presently accepted theories. But this may be about to change.<p>Physicists today describe the gravitational interaction through Einstein’s Theory of …

Dark Matter

Reproducible Data Analysis in Jupyter

Jupyter notebooks provide a useful environment for interactive exploration of data. A common question I get, though, is how you can progress from …

Python Programming

First hint of how DNA calculators could supercharge computing

By making DNA endlessly change, researchers have shown how a biological computer might one day solve problems much faster than conventional computers …

Quantum Computing

Deconstructing Deep Meta Learning

This article explores in more detail the idea of Meta Learning that was previously introduced in a post “The Meta Model and Meta Meta Model of Deep …

The MIT Probabilistic Computing Project

9.S915: Introduction to Probabilistic Programming<p>Introduces probabilistic programming, a computational formulation of probability theory. Covers how …

Searchable Datasets in Python: Images across Domains, Experiments, Algorithms, and Learning

When you hear about searching, chances are the first image that pops into your mind is a web browser and a web search engine. From ancient Alta Vista …

Machine Learning