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How to tune hyperparameters with Python and scikit-learn
In last week’s post, I introduced the k-NN machine learning algorithm which we then applied to the task of image classification. Using the k-NN algorithm, we obtained 57.58% classification accuracy on...
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An intro to linear classification with Python
Over the past few weeks, we’ve started to learn more and more about machine learning and the role it plays in computer vision, image classification, and deep learning. We’ve seen how Convolutional...
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Multi-class SVM Loss
A couple weeks ago,we discussed the concepts of both linear classification and parameterized learning. This type of learning allows us to take a set of input data and class labels, and actually learn...
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Softmax Classifiers Explained
Last week, we discussed Multi-class SVM loss; specifically, the hinge loss and squared hinge loss functions. A loss function, in the context of Machine Learning and Deep Learning, allows us to...
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Understanding regularization for image classification and machine learning
In previous tutorials, I’ve discussed two important loss functions: Multi-class SVM loss and cross-entropy loss (which we usually refer to in conjunction with Softmax classifiers). In order to to keep...
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A simple neural network with Python and Keras
Image Source If you’ve been following along with this series of blog posts, then you already know what a huge fan I am of Keras. Keras is a super powerful, easy to use Python library for building...
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Gradient descent with Python
Every relationship has its building blocks. Love. Trust. Mutual respect. Yesterday, I asked my girlfriend of 7.5 years to marry me. She said yes. It was quite literally the happiest day of my life. I...
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Stochastic Gradient Descent (SGD) with Python
In last week’s blog post, we discussed gradient descent, a first-order optimization algorithm that can be used to learn a set of classifier coefficients for parameterized learning. However, the...
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Intersection over Union (IoU) for object detection
Today’s blog post is inspired from an email I received from Jason, a student at the University of Rochester. Jason is interested in building a custom object detector using the HOG + Linear SVM...
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ImageNet: VGGNet, ResNet, Inception, and Xception with Keras
A few months ago I wrote a tutorial on how to classify images using Convolutional Neural Networks (specifically, VGG16) pre-trained on the ImageNet dataset with Python and the Keras deep learning...
View ArticleClik here to view.
An intro to linear classification with Python
Over the past few weeks, we’ve started to learn more and more about machine learning and the role it plays in computer vision, image classification, and deep learning. We’ve seen how Convolutional...
View ArticleClik here to view.
Multi-class SVM Loss
A couple weeks ago,we discussed the concepts of both linear classification and parameterized learning. This type of learning allows us to take a set of input data and class labels, and actually learn...
View ArticleClik here to view.
Softmax Classifiers Explained
Last week, we discussed Multi-class SVM loss; specifically, the hinge loss and squared hinge loss functions. A loss function, in the context of Machine Learning and Deep Learning, allows us to...
View ArticleClik here to view.
Understanding regularization for image classification and machine learning
In previous tutorials, I’ve discussed two important loss functions: Multi-class SVM loss and cross-entropy loss (which we usually refer to in conjunction with Softmax classifiers). In order to to keep...
View ArticleClik here to view.
A simple neural network with Python and Keras
Image Source If you’ve been following along with this series of blog posts, then you already know what a huge fan I am of Keras. Keras is a super powerful, easy to use Python library for building...
View ArticleClik here to view.
Gradient descent with Python
Every relationship has its building blocks. Love. Trust. Mutual respect. Yesterday, I asked my girlfriend of 7.5 years to marry me. She said yes. It was quite literally the happiest day of my life. I...
View ArticleClik here to view.
Stochastic Gradient Descent (SGD) with Python
In last week’s blog post, we discussed gradient descent, a first-order optimization algorithm that can be used to learn a set of classifier coefficients for parameterized learning. However, the...
View ArticleClik here to view.
Intersection over Union (IoU) for object detection
Today’s blog post is inspired from an email I received from Jason, a student at the University of Rochester. Jason is interested in building a custom object detector using the HOG + Linear SVM...
View ArticleClik here to view.
ImageNet: VGGNet, ResNet, Inception, and Xception with Keras
A few months ago I wrote a tutorial on how to classify images using Convolutional Neural Networks (specifically, VGG16) pre-trained on the ImageNet dataset with Python and the Keras deep learning...
View ArticleClik here to view.
Deep learning on the Raspberry Pi with OpenCV
I’ve received a number of emails from PyImageSearch readers who are interested in performing deep learning in their Raspberry Pi. Most of the questions go something like this: Hey Adrian, thanks for...
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