Article
Generative models are a family of AI architectures whose aim is to create data samples from scratch. They achieve this by capturing the data distributions of the type of things we want to generate. These kinds of models are being heavily researched, and there is a huge amount of hype...
Daniele Paliotta
Machine Learning is gaining popularity and usage over the globe. It has already drastically changed the way certain applications are built and will likely continue to be a huge (and increasing) part of our daily lives. There's no sugarcoating it, Machine Learning isn't simple. It's pretty daunting and can seem...
David Landup
TensorFlowis a well-established Deep Learning framework, and Keras is its official high-level API that simplifies the creation of models. Image recognition/classification is a common task, and thankfully, it's fairly straightforward and simple with Keras. In this guide, we'll take a look at how to classify/recognize images in Python...
Dan Nelson
TensorFlow is a deep learning framework that provides an easy interface to a variety of functionalities, required to perform state of the art deep learning tasks such as image recognition, text classification and so on. It is a machine learning framework developed by Google and is used for designing, building,...
Nicholas Samuel
This is the final article on using machine learning in Python to make predictions of the mean temperature based off of meteorological weather data retrieved from Weather Underground as described in part one of this series. The topic of this final article will be to build a neural network regressor...
Adam McQuistan
TensorFlow is an open-source library for machine learning applications. It's the Google Brain's second generation system, after replacing the close-sourced DistBelief, and is used by Google for both research and production applications. TensorFlow applications can be written in a few languages: Python, Go, Java and C. This post is concerned...
Mihajlo Pavloski
Training a deep neural network model could take quite some time, depending on the complexity of your model, the amount of data you have, the hardware you're running your models on, etc. On most of the occasions you'll need to save your progress to a file, so in case of...
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