By Mehmet Suzen, Theoretical Physicist, Research Scientist. Occams razor or principle of parsimony has been the guiding principle in statistical model…

Continue Reading# network

## Considerations for Effective AI in Mobile Networks

It’s a subject of ongoing research, but comes down to the robustness of the system. A robust system needs to…

Continue Reading## David Gündisch

Writing your first Generative Adversarial Network with Keras. How to beat facial recognition systems with Face Anonymization. Writing your first Neural…

Continue Reading## Matthew Stewart, PhD Researcher

Guide to R and Python in a Single Jupyter NotebookAdvanced Topics in Neural NetworksAn introduction to some advanced neural network topics such as…The…

Continue Reading## Recurrent Neural Networks (RNNs)

Recurrent Neural Networks (RNNs)Implementing an RNN from scratch in Python. Javaid NabiBlockedUnblockFollowFollowingJul 11The main objective of this post is to implement an…

Continue Reading## Gaining insights on transfer learning with FlashTorch

If you’ve done the maths already… I would be better of randomly guessing it myself. Intuitively, this perhaps makes sense.…

Continue Reading## Fashion product image classification using Neural Networks | Machine Learning from Scratch (Part VI)

The prediction is correct!Classifying ImagesBuilding a Neural NetworkOur Neural Network will have only 1 hidden layer. We will implement a somewhat…

Continue Reading## Neural Network Optimization

Neural Network OptimizationCovering optimizers, momentum, adaptive learning rates, batch normalization, and more. Matthew Stewart, PhD ResearcherBlockedUnblockFollowFollowingJun 27“The goal is to hit…

Continue Reading## Neural Networks with push button, AI for all

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

Continue Reading## 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