In this tutorial you will learn how to train a simple Convolutional Neural Network (CNN) with Keras on the Fashion MNIST dataset, enabling you to classify fashion images and categories. The Fashion MNIST dataset is meant to be a (slightly more challenging) drop-in replacement for the (less challenging) MNIST dataset. Similar to the MNIST digit […]
Keras: Multiple Inputs and Mixed Data
In this tutorial, you will learn how to use Keras for multi-input and mixed data. You will learn how to define a Keras architecture capable of accepting multiple inputs, including numerical, categorical, and image data. We’ll then train a single end-to-end network on this mixed data. Today is the final installment in our three part […]
macOS Mojave: Install TensorFlow and Keras for Deep Learning
Inside this tutorial, you will learn how to configure macOS Mojave for deep learning. After you’ve gone through this tutorial, your macOS Mojave system will be ready for (1) deep learning with Keras and TensorFlow, and (2) ready for Deep Learning for Computer Vision with Python. A tutorial on configuring Mojave has been a long time […]
Ubuntu 18.04: Install TensorFlow and Keras for Deep Learning
Inside this tutorial you will learn how to configure your Ubuntu 18.04 machine for deep learning with TensorFlow and Keras. Configuring a deep learning rig is half the battle when getting started with computer vision and deep learning. I take pride in providing high-quality tutorials that can help you get your environment prepared to get […]
Keras, Regression, and CNNs
In this tutorial, you will learn how to train a Convolutional Neural Network (CNN) for regression prediction with Keras. You’ll then train a CNN to predict house prices from a set of images. Today is part two in our three-part series on regression prediction with Keras: Part 1: Basic regression with Keras — predicting house prices […]
Regression with Keras
In this tutorial, you will learn how to perform regression using Keras and Deep Learning. You will learn how to train a Keras neural network for regression and continuous value prediction, specifically in the context of house price prediction. Today’s post kicks off a 3-part series on deep learning, regression, and continuous value prediction. We’ll […]
Machine Learning in Python
Struggling to get started with machine learning using Python? In this step-by-step, hands-on tutorial you will learn how to perform machine learning using Python on numerical data and image data. By the time you are finished reading this post, you will be able to get your start in machine learning. To launch your machine learning […]
Auto-Keras and AutoML: A Getting Started Guide
In this tutorial, you will learn how to use Auto-Keras, an open source alternative to Google’s AutoML, for automated machine learning and deep learning. When training a neural network on a dataset there are two primary objectives a deep learning practitioner is trying to optimize and balance: Defining a neural network architecture that lends itself […]
Keras Conv2D and Convolutional Layers
In today’s tutorial, we are going to discuss the Keras Conv2D class, including the most important parameters you need to tune when training your own Convolutional Neural Networks (CNNs). From there we are going to use the Keras Conv2D class to implement a simple CNN. We’ll then train and evaluate this CNN on the CALTECH-101 […]
How to use Keras fit and fit_generator (a hands-on tutorial)
In this tutorial, you will learn how the Keras .fit and .fit_generator functions work, including the differences between them. To help you gain hands-on experience, I’ve included a full example showing you how to implement a Keras data generator from scratch. Today’s blog post is inspired by PyImageSearch reader, Shey. Shey asks: Hi Adrian, thanks […]