In this tutorial, you will learn how to perform anomaly/novelty detection in image datasets using OpenCV, Computer Vision, and the scikit-learn machine learning library. Imagine this — you’re fresh out of college with a degree in Computer Science. You focused your studies specifically on computer vision and machine learning. Your first job out of school […]
Tag Archives | machine learning
Online/Incremental Learning with Keras and Creme
In this tutorial, you will learn how to perform online/incremental learning with Keras and Creme on datasets too large to fit into memory. A few weeks ago I showed you how to use Keras for feature extraction and online learning — we used that tutorial to perform transfer learning and recognize classes the original CNN was […]
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 – Save and Load Your Deep Learning Models
In this tutorial, you will learn how to save and load your Keras deep learning models. This blog post was inspired by PyImageSearch reader, Mason, who emailed in last week and asked: Adrian, I’ve been going through your blog and reading your deep learning tutorials. Thanks for them. I have a question though: After training, […]
Deep Learning and Medical Image Analysis with Keras
In this tutorial, you will learn how to apply deep learning to perform medical image analysis. Specifically, you will discover how to use the Keras deep learning library to automatically analyze medical images for malaria testing. Such a deep learning + medical imaging system can help reduce the 400,000+ deaths per year caused by malaria. […]
YOLO object detection with OpenCV
In this tutorial, you’ll learn how to use the YOLO object detector to detect objects in both images and video streams using Deep Learning, OpenCV, and Python. By applying object detection, you’ll not only be able to determine what is in an image, but also where a given object resides! We’ll start with a brief […]
OpenCV Face Recognition
In this tutorial, you will learn how to use OpenCV to perform face recognition. To build our face recognition system, we’ll first perform face detection, extract face embeddings from each face using deep learning, train a face recognition model on the embeddings, and then finally recognize faces in both images and video streams with OpenCV. […]
Keras Tutorial: How to get started with Keras, Deep Learning, and Python
Inside this Keras tutorial, you will discover how easy it is to get started with deep learning and Python. You will use the Keras deep learning library to train your first neural network on a custom image dataset, and from there, you’ll implement your first Convolutional Neural Network (CNN) as well. The inspiration for this […]
Semantic segmentation with OpenCV and deep learning
In this tutorial, you will learn how to perform semantic segmentation using OpenCV, deep learning, and the ENet architecture. After reading today’s guide, you will be able to apply semantic segmentation to images and video using OpenCV. Deep learning has helped facilitate unprecedented accuracy in computer vision, including image classification, object detection, and now even […]