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 […]