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python

Get Started Developing for Quantum Computers with Q# and Python

In case you missed it, here is Sarah Kaiser’s live Twitch coding stream recap.   For more, check out the book: Learn Quantum Computing with Python and Q#. For more live coding streams, subscribe to Manning’s Twitch channel here: https://www.twitch.tv/manningpublications… Continue Reading →

Deploying Machine Learning Models, Part 5: deployment

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.

Deploying Machine Learning Models, Part 4: creating a Docker image

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.

Deploying Machine Learning Models, Part 3: managing dependencies

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…. Continue Reading →

Deploying Machine Learning Models, Part 2: model serving

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.

Converting Pure Deep Learning with PyTorch to Use Lightning and Hangar

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.

Deploying Machine Learning Models, Part 1: saving models

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.

Sentiment Classification Using a Large Movie Review Dataset, Part 2

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 →

Hands-On Deep Learning Model Training

In this video, we join deep learning advocate Mark Ryan on his tour into training the model and running experiments.

Pandas in One Hour

In this video, Boris Paskhaver showcases the high-level features of the Pandas library.

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