Because the code was deeply coupled with response data models. At this time, I didn’t want to make the same…

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## Word2vec from Scratch with NumPy

Word2vec from Scratch with NumPyHow to implement a Word2vec model with Python and NumPyIvan ChenBlockedUnblockFollowFollowingFeb 17IntroductionRecently, I have been working with several…

Continue Reading## Backpropagation for people who are afraid of math

We will go over each expression. When trying to update and optimize the network’s weights, we are trying to find-,…

Continue Reading## What the heck is Word Embedding

What the heck is Word EmbeddingLooking at text data through the lens of Neural NetsSamarth AgrawalBlockedUnblockFollowFollowingFeb 10Photo by Dmitry Ratushny on UnsplashWord…

Continue Reading## The keys of Deep Learning in 100 lines of code

Yes, and from scratch, using the Python programming language in this case. So let’s go for it, and in the…

Continue Reading## Generative Adversarial Networks (GANs) for Beginners

A GAN consist of two types of neural networks: a generator and discriminator. The GeneratorThe generator’s job is to take…

Continue Reading## Neural Networks: The theoretical understanding

Neural Networks: The theoretical understandingAbhishek ShuklaBlockedUnblockFollowFollowingDec 28, 2018This article is for students or professionals who want to learn neural networks…

Continue Reading## How to Develop Deep Learning Neural Networks With Greedy Layer-Wise Pretraining

Training deep neural networks was traditionally challenging as the vanishing gradient meant that weights in layers close to the input…

Continue Reading## Bayesian CNN model on MNIST data using Tensorflow-probability (compared to CNN)

Bayesian CNN model on MNIST data using Tensorflow-probability (compared to CNN)LU ZOUBlockedUnblockFollowFollowingJan 29MotivationI’ve been recently reading about the Bayesian neural network…

Continue Reading## Sentiment Analysis with Word Bags and Word Sequences

That is the question we explore here. We start with a simpler binary classification task in this post and consider…

Continue Reading## A must-read tutorial when you are starting your journey with Deep Learning

Let’s calculate it. Note that there are 784 connections to each neuron from hidden layer, each combination having an associated…

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

It’s getting the gradients for each step. And with the slopes, we will update the weights as we talked above.…

Continue Reading## Sentiment Classification with Natural Language Processing on LSTM

")feature_result_tgt = nfeature_accuracy_checker(vectorizer=tfidf,ngram_range=(1, 3))Before we are done here, we should check the classification report. from sklearn. metrics import classification_reportcv =…

Continue Reading## Back Propagation, the Easy Way (Part 1)

for each neuron of each layer. So now variable with only superscript letter such as ????ᴸ, w ˡ are vectors…

Continue Reading## A Deep Dive Into Data Quality

A Deep Dive Into Data QualityGary CBlockedUnblockFollowFollowingJan 3Introduction:Data quality is often seen as the unglamorous component to working with data. Ironically,…

Continue Reading## Running R on AWS Lambda

Photo by Cris DiNoto on UnsplashRunning R on AWS LambdaPhilipp SchirmerBlockedUnblockFollowFollowingDec 5, 2018R is one of the most popular programming languages for…

Continue Reading## Predicting Invasive Ductal Carcinoma using Convolutional Neural Network (CNN) in Keras

Predicting Invasive Ductal Carcinoma using Convolutional Neural Network (CNN) in KerasClassifying histopathology slides as malignant or benign using CNNBikram BaruahBlockedUnblockFollowFollowingJan 3In this…

Continue Reading## Visual Interpretability for Convolutional Neural Networks

The Jupyter notebook for each visualization is written in Keras and is available in my GitHub repository:himanshurawlani/convnet-interpretability-kerasVisualizing VGG16 Convolutional Neural…

Continue Reading## Convolutional Neural Network

ANN Calculation for each layerwhere,x — is the input vector with dimension [p_l, 1]W — Is the weight matrix with dimensions [p_l, n_l] where, p_l…

Continue Reading## Why Did We Shift Away From Database-Generated Ids?

So, every time we want to create a new record, the database engine automatically creates a primary key, and it’s…

Continue Reading## Building your own Artificial Neural Network from scratch on Churn Modeling Dataset using Keras in Python

Redo more Epochs.Importing the Keras libraries and packagesimport kerasFor building the Neural Network layer by layerfrom keras.models import SequentialTo randomly initialize…

Continue Reading## A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way

The advancements in Computer Vision with Deep Learning has been constructed and perfected with time, primarily over one particular algorithm — a…

Continue Reading## Using CNNs and RNNs for Music Genre Recognition

This model passes the input spectogram through both CNN and RNN layers in parallel, concatenating their output and then sending…

Continue Reading## Building a carbon molecule autoencoder

Unlabeled data is perfect for unsupervised learning, where input data does not need to come with a preassigned corresponding list…

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