From Machine Learning Bookcamp by Alexey Grigorev
In this series, we cover model deployment: the process of putting models to use. In particular, we’ll see how to package a model inside a web service, allowing other services to use it. We also show how to deploy the web service to a production-ready environment.
In this video, machine learning expert Eli Stevens showcases how to use open-source libraries that are available in the PyTorch ecosystem to cut down the amount of the code that you want to write.
From Machine Learning Bookcamp by Alexey Grigorev
In this series, we cover model deployment: the process of putting models to use. In particular, we’ll see how to package a model inside a web service, allowing other services to use it. We also show how to deploy the web service to a production-ready environment.
From Machine Learning with TensorFlow, Second Edition by Chris Mattmann This article covers: Building sentiment classifier using logistic regression and with softmax Measuring classification accuracy Computing ROC curve and measure classifier effectiveness Submitting your results to the Kaggle challenge for… Continue Reading →
In this video, we join deep learning advocate Mark Ryan on his tour into training the model and running experiments.
In this video, Boris Paskhaver showcases the high-level features of the Pandas library.
From Machine Learning with TensorFlow, Second Edition by Chris Mattmann
This article covers using text and word frequency (Bag of Words) to represent sentiment.
In this tour de force live coding session, an expert Python coach Reuven Lerner shows you how functions work behind the scenes and how you can use them in different ways.
By Dennis Byrne
This article explores securing data using keyed hashing in Python.
Deep dive with Carl Osipov into understanding automatic differentiation used by PyTorch autograd for deep learning