Questions tagged [neural-network]
In machine learning and cognitive science, neural networks are a family of statistical learning models inspired by biological neural networks and are used to estimate or approximate functions that can depend on a large number of inputs and are generally unknown.
112 questions
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Time series prediction by LSTM model
I have a collection of TEC data. My data sample for example: day1, day2, day3, day4.
Case1:
I have the following task to do: Training by the consecutive 3 days to predict the each 4th day. Each day ...
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Graph Neural Network (GNN) (2) [duplicate]
This is an implementation of a graph neural network.
Edges are represented by an egde-list.
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Graph Neural Network (GNN) (1)
The given datasets are graph data structure that represents social interactions.
The nodes will be represented as People{node_id, edge, gender, occupation} and the ...
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Neural network text classifier
I wrote a simple NN text classifier to help me quickly sort through the new daily submissions to the arXiv. It
downloads the new submissions, processings their titles and abstracts,
trains a NN on ...
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Feature subset selection using neural network
This listing selects the best features from the 1011 available columns in a given dataset.
The first three columns are dropped because they are useless data.
The dataset is huge. So, they were read in ...
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One-layer linear neural network to solve a regression problem in PyTorch
Good morning everyone,
I am trying to figure out how deep learning works. My approach is mainly theoretical but I have decided to code a few deep learning projects to get a better feel of the kind of ...
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Custom neural network implementation in TensorFlow to compare normalisation vs. no normalisation on data
I am performing a sports prediction multi-class classification problem, and wanted to compare the differences in model performance between normalised and non-normalised data. You can see the 2 ...
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A simple word embedder only using jax
How can this code be improved? I'm a novice programmer trying to learn ml by doing it from scratch. This code is part of a transformer model that I'm working on. Do you have any ideas about how to ...
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Feed forward neural network
I have made a basic neural network in python. The idea is the neural network can have any structure you want, not just the standard layers where every neuron is connected to every neuron in the next ...
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ANN with Backpropagation for MINST data set
I am learning about ANN and tried it for the MINST data sets. Now I am supposted to create a neural network (ANN) with backpropagation.
The structure for the neural network I have is this the input ...
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Neural Network in Julia (Multilayer Perceptron)
I wrote a simple multilayer perceptron in Julia, which seems to work fine on different datasets, e.g. the MNIST dataset with a success rate of about 90% after a few seconds of training. But I would ...
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Optimize an algorithm for preparing a dataset for machine learning
I'm learning how to use R coming from a python background. I'm following Andrej Karpathy's zero-to-hero course, reimplementing it in R.
We start with a list of 32033 names. These names have to be ...
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Readable Backprogragation calculations in Numpy Neural Network
As an exercise we should write a small Neural Network with the following structure:
There should be additionally a bias for each layer and sigmoid should be used as the activation function.
The ...
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Neural network that determines the gender of a word
I wrote a neural network in Python using PyTorch which determines the gender of a word in Russian. As a training set: a file containing a word and a number from 0 to 2 (0-masculine, 1-feminine and 2-...
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Binary classification with pytorch
I wrote a simple neural network binary classification algorithm using Pytorch. It uses the dataset from https://www.kaggle.com/pritsheta/heart-attack, which consists of a table with 300 rows and 14 ...
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