Dante Alexis

126 Flips | 13 Magazines | 1 Like | 6 Followers | @Karamix2 | Keep up with Dante Alexis on Flipboard, a place to see the stories, photos, and updates that matter to you. Flipboard creates a personalized magazine full of everything, from world news to life’s great moments. Download Flipboard for free and search for “Dante Alexis”

‘Minimalist machine learning’ algorithm analyzes complex microscopy and other images from very little data

(a) Raw microscopy image of a slice of mouse lymphblastoid cells. (b) Reconstructed image using time-consuming manual segmentation — note missing …

Machine Learning

Machine Learning Explained: Understanding Supervised, Unsupervised Reinforcement Learning

Machine Learning Explained: Understanding Supervised, Unsupervised & Reinforcement Learning<p>Machine Learning is guiding Artificial Intelligence …

Black-box optimization — Graduate Descent

Black-box optimization algorithms are a fantastic tool that everyone should be aware of. I frequently use black-box optimization algorithms for …

Android P drops support for Nexus 5X, Nexus 6P, and the Pixel C tablet

Developers looking to get a jump on upcoming Android features have a small set of blessed hardware to choose from with Android P: the Pixel, Pixel XL, Pixel 2, and Pixel 2 XL.<p>Eventually, Android P will ship on new phones from other manufacturers, along with the handful of handsets that …

Android News

Unlock a career in ethical hacking with these five courses

When it comes to keeping cybercriminals at bay, the best solution is to employ hackers who use the same skills for good. Commonly known as ethical …

Image Recognition and Object Detection

In this latest blog, I’m responding to a cry for help. Someone got in touch with us recently asking for some advice on image detection algorithms, so …

Tracing fake news footprints: characterizing social media messages by how they propagate

Tracing fake news footprints: characterizing social media messages by how they propagate Wu & Liu, <i>WSDM’18</i>This week we’ll be looking at some of the …

Social Media

Redditors Are Putting Nic Cage Into Every Movie Using Machine Learning

It can only get worse.<p>In December, a horny trend began hatching on Reddit thanks to one user’s ability to use machine learning algorithms to create …

Deep Generative Models

A Generative Model is a powerful way of learning any kind of data distribution using unsupervised learning and it has achieved tremendous success in …

'The Truth About Getting Fit': Five Exercise Lessons From The BBC Show

Spoiler: doing 10,000 steps might not be the best way to up your fitness.<p>Improving your fitness doesn’t demand marathon-length runs or spending every …

Exercise

Simple(x) Global Optimization

Quick rundown:<p>Simple is a radically more scalable alternative to Bayesian Optimization. Like Bayesian Optimization, it is highly sample-efficient, …

Data Science

Autoencoders and Sparsity - Ufldl

From Ufldl<p>Jump to: navigation, search<p>So far, we have described the application of neural networks to supervised learning, in which we have labeled …

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. (arXiv:1801.08116v2 [cs.AI] UPDATED)

Authors: Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel …

Machine Learning

How to solve 90% of NLP problems: a step-by-step guide

<b>This post is accompanied by</b> <b>an interactive notebook</b> <b>demonstrating and applying all these techniques. Feel free to run the code and follow along!</b><p>Step 1: …

Natural Language Processing

The scanner that looks deep

As the healthcare industry expands, the volume of data and complexity of diagnostic imaging (X-rays, MRIs and CT scans) is increasing, while the …

Deep Learning

Kernel Feature Selection via Conditional Covariance Minimization

Jianbo Chen and Mitchell Stern Jan 23, 2018<p>Feature selection is a common method for dimensionality reduction that encourages model interpretability. …

Algorithms

Algorithms show potential in measuring diagnostic errors using big data

While the problem of diagnostic errors is widespread in medicine, with an estimated 12 million Americans affected annually, a new approach to …

Preparing continuous features for neural networks with GaussRank

We present a novel method for feature transformation, akin to standardization. The method comes from Michael Jahrer, who recently has won another …

Fast and Accurate Face Tracking in Live Video with Python

Fast and Accurate Face Tracking in Live Video with Python<p>Follow Glenn • 72 days ago<br>8 Projects • 6 Followers<p>I recently came across a post on Reddit …

Deep Learning in Computer Vision

<b>About this course:</b> Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new …

Transfer Learning: Leverage Insights from Big Data

In this tutorial, you’ll see what transfer learning is, what some of its applications are and why it is critical skill as a data scientist.

Machine Learning

ONC: Artificial Intelligence Has Potential to Reshape Healthcare

Artificial intelligence is playing an increasingly important role in healthcare analytics and will continue to dramatically influence the development …

Digital Health

5 Innovative Uses for Machine Learning

They'll be coming into your life -- at least your business life -- sooner than you think.<p>Opinions expressed by <i>Entrepreneur</i> contributors are their own.<p>Though its time horizon can't be predicted, artificial intelligence (AI) promises to foundationally influence modern society, for better or worse. A …

Faster R-CNN: Down the rabbit hole of modern object detection

The input images are represented as \mathit{Height} \times \mathit{Width} \times \mathit{Depth} tensors (multidimensional arrays), which are passed …

The Generalization Mystery: Sharp vs Flat Minima

I set out to write about the following paper I saw people talk about on twitter and reddit:• Hao Li, Zheng Xu, Gavin Taylor, Tom Goldstein Visualizing …

Deep Learning

An Intuitive Introduction to Generative Adversarial Networks

<i>This article was jointly written by Keshav Dhandhania and Arash Delijani, bios below.</i>In this article, I’ll talk about <b>Generative Adversarial Networks</b>, …

Deep Learning

The 10 Statistical Techniques Data Scientists Need to Master

This was a basic run-down of some basic statistical techniques that can help a data science program manager and or executive have a better …

Data Science

Neuroscientists Have Followed a Thought as It Moves Through The Brain

We didn't think it was possible.<p>A study using epilepsy patients undergoing surgery has given neuroscientists an opportunity to track in unprecedented …

Sequence Models