Mastering MLOps: Live Model Deployment & Inference Course with Stefan Krawczyk

Sponsored Post AI & Machine Learning now power most product experiences even beyond those of the big technology companies. Today, your models must perform and function correctly to ultimately deliver business value. The cost of deploying a slow or bad model, or not detecting undesirable behavior quickly, could significantly impact customer experience and the business’ […]

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Tepper Wants to Nerd Out On Data With You

Sponsored Post There are many practical reasons why you should choose an online Masters in Business Analytics from the Tepper School of Business at Carnegie Mellon University. We can list facts like: our alumni average $103,000 in starting salary and 84% of our grads secured a promotion or new position within three months of graduation. […]

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Example MNIST images

Image Augmentation for Deep Learning with Keras

Data preparation is required when working with neural networks and deep learning models. Increasingly, data augmentation is also required on more complex object recognition tasks. In this post, you will discover how to use data preparation and data augmentation with your image datasets when developing and evaluating deep learning models in Python with Keras. After […]

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Loss function

Loss Functions in TensorFlow

The loss metric is very important for neural networks. As all machine learning models are one optimization problem or another, the loss is the objective function to minimize. In neural networks, the optimization is done with gradient descent and backpropagation. But what are loss functions, and how are they affecting your neural networks? In this […]

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Understanding the Design of a Convolutional Neural Network

Convolutional neural networks have been found successful in computer vision applications. Various network architectures are proposed, and they are neither magical nor hard to understand. In this tutorial, you will make sense of the operation of convolutional layers and their role in a larger convolutional neural network. After finishing this tutorial, you will learn: How […]

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Using Learning Rate Schedules for Deep Learning Models in Python with Keras

Using Learning Rate Schedules for Deep Learning Models in Python with Keras

Training a neural network or large deep learning model is a difficult optimization task. The classical algorithm to train neural networks is called stochastic gradient descent. It has been well established that you can achieve increased performance and faster training on some problems by using a learning rate that changes during training. In this post, […]

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