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numpy meshgrid loss surface

NumPy Meshgrid: Understanding np.meshgrid()

You can create multi-dimensional coordinate arrays using the np.meshgrid() function, which is also available in PyTorch and TensorFlow. But watch out! PyTorch uses different indexing by default so the results might not be the same.

SageMaker Studio Quick Start

A step-by-step quick start guide for SageMaker Studio. Start a Studio session, launch a notebook on a GPU instance and run object detection inference with a detectron2 pre-trained model.

Numpy Pad: Understanding np.pad()

The np.pad() function has a complex, powerful API. But basic usage is very simple and complex usage is achievable! This post shows you how to use NumPy pad and gives a couple examples.

Installing Packages in a Jupyter Notebook

This post describes a trick for installing/upgrading Python packages in a Jupyter notebook. It’s useful for scratch code, but don’t do this when you need reproducible code.

normalized cat image pytorch

Normalizing Images in PyTorch

You can use the torchvision Normalize() transform to subtract the mean and divide by the standard deviation for image tensors in PyTorch. But it’s important to understand how the transform works and how to reverse it.

Dropping Columns and Rows in Pandas

There are a few ways to drop columns and rows in Pandas. This post describes the easiest way to do it and provides a few alternatives that can sometimes be useful.

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