Neural Networks with push button, AI for allNeural Architecture Search with NASBench from Google Research— Can we design network architectures automatically,…

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## Do Conv-nets Dream of Psychedelic Sheep?

By Kevin Vu, Exxact Corp. Deep dreaming at successive layers of abstraction. From top to bottom: input image, conv2-3x3_reduce, inception_4c-1×1.…

Continue Reading## LSTM: How To Train Neural Networks to Write like Lovecraft

I’ll explain it now, though I highly recommend you give those tutorials a chance too. How do LSTM cells work?An LSTM…

Continue Reading## Improving Deep Neural Networks

Improving Deep Neural NetworksRochak AgrawalBlockedUnblockFollowFollowingJun 19Deep Neural Networks are the solution to complex tasks like Natural Language Processing, Computer Vision, Speech…

Continue Reading## Classification Using Neural Networks

After reading this article you should have a rough understanding of the internal mechanics of neural nets, and convolution neural…

Continue Reading## Layman’s Introduction to Backpropagation

Layman’s Introduction to BackpropagationTraining a neural network is no easy feat but it can be simple to understand itRishi SidhuBlockedUnblockFollowFollowingJun…

Continue Reading## The Basics of Neural Networks with Tensorflow

The Basics of Neural Networks with TensorflowChristopher KazakisBlockedUnblockFollowFollowingJun 5Today, we’re going to learn the basic ideas behind how a neural…

Continue Reading## CNN Heat Maps: Class Activation Mapping (CAM)

CNN Heat Maps: Class Activation Mapping (CAM)Rachel Lea Ballantyne DraelosBlockedUnblockFollowFollowingJun 11This is the first post in an upcoming series about different…

Continue Reading## Network Science & Threat Intelligence with Python: Network Analysis of Threat Actors/Malware Strains (Part 1)

And more specifically, threat intelligence?Well, we plot hundreds and thousands of attributes and relationships within threat intelligence. The amount of…

Continue Reading## Step-by-step understanding LSTM Autoencoder layers

Step-by-step understanding LSTM Autoencoder layersHere we will break down an LSTM autoencoder network to understand them layer-by-layer. We will go…

Continue Reading## Knowing Your Neighbours: Machine Learning on Graphs

We can broadly classify the kinds of problems connected data can solve into four categories:Node ClassificationLink PredictionCommunity DetectionGraph ClassificationThere exist…

Continue Reading## Understanding Neural Networks

In the next section, we will see how backpropagation helps us deal with this problem. Quick Review of Gradient DescentThe gradient…

Continue Reading## One LEGO at a Time: Explaining the Math of how Neural Networks Learn with Implementation from Scratch

Demystifying the Math Behind Neural Nets | Towards AIOne LEGO at a Time: Explaining the Math of how Neural Networks Learn…

Continue Reading## Introduction to Neural Networks

Recall that bias signifies addition. The bias value assigned to this layer is -2. That means we subtract 2 from…

Continue Reading## Introduction to Neural Networks — Part 1

It is essentially a naive implementation of how our brains might work. It’s not a very accurate representation but it…

Continue Reading## Decoding the Best Papers from ICLR 2019 – Neural Networks are Here to Rule

This is because the architectures uncovered by pruning are harder to train from the beginning and bring down the…

Continue Reading## Moving from Keras to Pytorch

It's not that difficult. Rahul AgarwalBlockedUnblockFollowFollowingMay 28Photo by David Clode on UnsplashPytorch is great. But it doesn’t make things easy for…

Continue Reading## Building a neural network that learns to play a game — Part 1

That is clearly impressive as the difference between the two videos is just of a few minutes. Now, let’s discuss…

Continue Reading## #Fail: Artificial Intelligence is a Science

Is it worth it?Frustratingly, we did some testing of this idea last year and failed to get the approach working.…

Continue Reading## How to create a neural network from scratch in Python — Math & Code

For most functions, in fact we can’t know. Here, the trick comes from a theorem demonstrated by Kurt Hornik called…

Continue Reading## Neural Networks — A Solid Practical Guide

Neural Networks — A Solid Practical GuideExplaining How Neural Networks Work With Practical ExamplesFarhad MalikBlockedUnblockFollowFollowingMay 16This article aims to present a transparent…

Continue Reading## Research of Influence in Offline and Online Social Networks

Research of Influence in Offline and Online Social NetworksThe role of tie strength and network degrees in determining the power of…

Continue Reading## How the Lottery Ticket Hypothesis is Challenging Everything we Knew About Training Neural Networks

Paradoxically, practical experiences in machine learning solutions show that the architectures uncovered by pruning are harder to train from the…

Continue Reading## Five Methods to Debug your Neural Network

Five Methods to Debug your Neural NetworkSahil DhankhadBlockedUnblockFollowFollowingMay 3A lot of us trying to understand the Machine Learning Algorithms, but sometimes…

Continue Reading## Build your own neural network classifier in R

Build your own neural network classifier in RJun M. BlockedUnblockFollowFollowingApr 28IntroductionImage classification is one important field in Computer Vision, not only…

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