Deep learning was a recent invention. Partially, it is due to improved computation power that allows us to use more […]
Archive | Deep Learning Performance
How to Demonstrate Your Basic Skills with Deep Learning
Skills in deep learning are in great demand, although these skills can be challenging to identify and to demonstrate. Explaining […]
Why Training a Neural Network Is Hard
Or, Why Stochastic Gradient Descent Is Used to Train Neural Networks. Fitting a neural network involves using a training dataset […]
How to use Learning Curves to Diagnose Machine Learning Model Performance
A learning curve is a plot of model learning performance over experience or time. Learning curves are a widely used […]
Recommendations for Deep Learning Neural Network Practitioners
Deep learning neural networks are relatively straightforward to define and train given the wide adoption of open source libraries. Nevertheless, […]
8 Tricks for Configuring Backpropagation to Train Better Neural Networks
Neural network models are trained using stochastic gradient descent and model weights are updated using the backpropagation algorithm. The optimization […]
Neural Networks: Tricks of the Trade Review
Deep learning neural networks are challenging to configure and train. There are decades of tips and tricks spread across hundreds […]
How to Get Better Deep Learning Results (7-Day Mini-Course)
Better Deep Learning Neural Networks Crash Course. Get Better Performance From Your Deep Learning Models in 7 Days. Configuring neural […]
A Gentle Introduction to the Challenge of Training Deep Learning Neural Network Models
Deep learning neural networks learn a mapping function from inputs to outputs. This is achieved by updating the weights of […]
How to Control Neural Network Model Capacity With Nodes and Layers
The capacity of a deep learning neural network model controls the scope of the types of mapping functions that it […]