Learn and Contribute
It was with great pleasure that AI Singapore invited Aurélien…
Animated RNN, LSTM & GRU
Recurrent neural networks are a class of artificial neural networks…
10 Gradient Descent Optimisation Algorithms + Cheat Sheet
Gradient descent is an optimisation method for finding the minimum of a function. It is commonly used in deep learning models to update the weights of the neural network through backpropagation.
In this post, I will summarise the common gradient descent optimisation algorithms used in popular deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe). The purpose of this post is to make it easy to read and digest (using consistent nomenclature) since there aren’t many of such summaries out there, and as a cheat sheet if you want to implement them from scratch.
How I improved a Human Action Classifier to 80% Validation Accuracy in 6 Easy Steps
How many of you are master procrastinators? If you are, you…
Intel AI Academy
AI Singapore have partnered with Intel to offer the intel…
Converting a Simple Deep Learning Model from PyTorch to TensorFlow
Making your PyTorch models work in environments with only TensorFlow
Text-based Graph Convolutional Network — Bible Book Classification
A semi-supervised graph-based approach for text classification and inference The…
Simple Neural Network Model Using TensorFlow Eager Execution
The Eager way to building deep learning models
From-scratch implementation of AlphaZero for Connect4
Step-by-step illustration on how one can implement AlphaZero on games…
Object Detection for Product Images
Object detection using SSD300 models
Tutorial: Linear Regression with Stochastic Gradient Descent
Implementing backpropagation for linear regression with stochastic gradient descent in JavaScript
Intuitions on L1 and L2 Regularisation
Explaining how L1 and L2 work using gradient descent
