Using Depthwise Separable Convolutions in Tensorflow

Tweet Tweet Share Share Last Updated on August 4, 2022 Looking at all of the very large convolutional neural networks such as ResNets, VGGs, and the like, it begs the question on how we can make all of these networks smaller with less parameters while still maintaining the same level of accuracy...

1w

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

Tweet Tweet Share Share Last Updated on July 29, 2022 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...

2w

Tepper Wants to Nerd Out On Data With You

Tweet Tweet Share Share Last Updated on July 28, 2022 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...

2w

Image Augmentation with Keras Preprocessing Layers and tf.image

Tweet Tweet Share Share Last Updated on August 6, 2022 When you work on a machine learning problem related to images, not only do you need to collect some images as training data, but you also need to employ augmentation to create variations in the image. It is especially true for more complex...

4w

Loss Functions in TensorFlow

Tweet Tweet Share Share Last Updated on July 15, 2022 Loss metric is very important for neural networks. As all machine learning model is a optimization problem or another, the loss is the objective function to minimize. In neural networks, the optimization is done with gradient descent and...

4w

High-Fidelity Synthetic Data for Data Engineers and Data Scientists Alike

Tweet Tweet Share Share Last Updated on July 15, 2022 Sponsored Post If you’re a data engineer or data scientist, you know how hard it is to generate and maintain realistic data at scale. And to guarantee data privacy protection, in addition to all your day-to-day responsibilities? OOF. Talk...

Jul 2022

Understanding the Design of a Convolutional Neural Network

Tweet Tweet Share Share Last Updated on July 13, 2022 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, we will make sense of the operation...

Jul 2022

A Gentle Introduction to tensorflow.data API

Tweet Tweet Share Share Last Updated on July 12, 2022 When we build and train a Keras deep learning model, the training data can be provided in several different ways. Presenting the data as a NumPy array or a TensorFlow tensor is a common one. Making a Python generator function and let the...

Jul 2022

Using Activation Functions in Neural Networks

Tweet Tweet Share Share Last Updated on July 6, 2022 Activation functions play an integral role in neural networks by introducing non-linearity. This nonlinearity allows neural networks to develop complex representations and functions based on the inputs that would not be possible with a simple...

Jul 2022

Three Ways to Build Machine Learning Models in Keras

Tweet Tweet Share Share If you’ve looked at Keras models on Github, you’ve probably noticed that there are some different ways to create models in Keras. There’s the Sequential model which allows you to define an entire model in a single line, usually with some line breaks for readability, then...

Jul 2022