The convolutional layer in convolutional neural networks systematically applies filters to an input and creates output feature maps. Although the…

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## Master the basics of machine learning by solving a hackathon problem

Master the basics of machine learning by solving a hackathon problemLearn how to solve regression problem step by step and…

Continue Reading## A Gentle Introduction to Convolutional Layers for Deep Learning Neural Networks

Convolution and the convolutional layer are the major building blocks used in convolutional neural networks. A convolution is the simple…

Continue Reading## ToneNet : A Musical Style Transfer

ToneNet : A Musical Style TransferSuraj JayakumarBlockedUnblockFollowFollowingNov 27, 2017By: Team Vesta, University of Southern California. CSCI:599 Deep Learning and Its ApplicationsSuraj Jayakumar…

Continue Reading## How to Design Powerful Scripts in Genetics

How to Design Powerful Scripts in GeneticsUser input and Command Line Arguments made Simple- with PythonStephen FordhamBlockedUnblockFollowFollowingApr 11The design of a script…

Continue Reading## Symbolic vs Connectionist A.I.

Symbolic vs Connectionist A. I. Josef BajadaBlockedUnblockFollowFollowingApr 8As Connectionist techniques such as Neural Networks are enjoying a wave of popularity,…

Continue Reading## What’s Big O notation, faster runtime — Simply explained

As n grows the number of operations grows in correlation with n. Introduce Big OBig o is just a way to…

Continue Reading## Using PyTorch to Generate Images of Malaria-Infected Cells

For the VAE itself, we instantiate the layers in the __init__ section and define the layer interactions in the ‘forward’…

Continue Reading## Introduction to Convolutional Neural Networks (CNN) with TensorFlow

Introduction to Convolutional Neural Networks (CNN) with TensorFlowLearn the foundations of convolutional neural networks for computer vision and build a…

Continue Reading## Mixture of Variational Autoencoders — a Fusion Between MoE and VAE

MoE’s power stems from the fact that each expert specializes in a different segment of the input space with a…

Continue Reading## Attention in RNNs

Attention in RNNsUnderstanding the mechanism with a detailed exampleNir ArbelBlockedUnblockFollowFollowingMar 15Montepulciano ItalyRecurrent Neural Networks (RNNs) have been used successfully for many tasks…

Continue Reading## How Transformers Work

How Transformers WorkThe Neural Network used by Open AI and DeepMindGiuliano GiacagliaBlockedUnblockFollowFollowingMar 10Transformers are a type of neural network architecture that…

Continue Reading## Recurrent Neural Networks

Recurrent Neural NetworksRemembering what’s importantMahendran VenkatachalamBlockedUnblockFollowFollowingFeb 28Recurrent Neural Networks (RNNs) add an interesting twist to basic neural networks. A vanilla neural…

Continue Reading## Performing Classification in TensorFlow

Performing Classification in TensorFlowHarshdeep SinghBlockedUnblockFollowFollowingFeb 25In this article, I will explain how to perform classification using TensorFlow library in Python.…

Continue Reading## Language Translation with RNNs

Language Translation with RNNsBuild a recurrent neural network (RNN) to translate English to FrenchThomas TraceyBlockedUnblockFollowFollowingFeb 22Image credit: xiandong79. github. ioThis post explores…

Continue Reading## Generating extinct Japanese script with Adversarial Autoencoders: Theory and Implementation

Generating extinct Japanese script with Adversarial Autoencoders: Theory and ImplementationAdrian Yijie XuBlockedUnblockFollowFollowingFeb 18IntroductionBe it political deepfakes, near real-time video modification,…

Continue Reading## How the Embedding Layers in BERT Were Implemented

How the Embedding Layers in BERT Were Implemented___BlockedUnblockFollowFollowingFeb 19IntroductionIn this article, I will explain the implementation details of the embedding…

Continue Reading## A journey into Convolutional Neural Network visualization

In reality, the network learns to recognize the weather, not the enemy tanks. The source code can be found here.…

Continue Reading## Autoencoders: Neural Networks for Unsupervised Learning

Recall that the label of the decoder is now the label of this large neural network, and the label of…

Continue Reading## The Most Intuitive and Easiest Guide for Recurrent Neural Network

Speech, DNA chains, and time series. The answer is “sequential. ” The data is not static or discontinuous, but forgoing…

Continue Reading## How to Improve Neural Network Stability and Modeling Performance With Data Scaling

Neural Nets FAQIf your problem is a regression problem, then the output will be a real value. This is best…

Continue Reading## 7 easy steps to custom inputs in shiny

7 easy steps to custom inputs in shinyA step by step guide on how to include custom inputs into R Shiny.…

Continue Reading## Counting No. of Parameters in Deep Learning Models by Hand

Photo by Andrik Langfield on UnsplashCounting No. of Parameters in Deep Learning Models by Hand5 simple examples to count parameters in FFNN,…

Continue Reading## Must-Read Tutorial to Learn Sequence Modeling (deeplearning.ai Course #5)

Solving this gives us a 300 dimensional vector with a value equal to the embeddings of queen. We can use…

Continue Reading## A Python Programmers’ Guide to Dashboarding — Part 2

A Python Programmers’ Guide to Dashboarding — Part 2Controls and Callbacks & Organizational PropertiesDrimik RoyBlockedUnblockFollowFollowingJan 7Written by: Drimik Roy & Namrata Chaudhary — January 7,…

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