PyTorch

Computer Vision Deep Learning

PyTorch and Monai for AI Healthcare Imaging – Python Machine Learning Course

Learn how to use PyTorch, Monai, and Python for computer vision using machine learning. One practical use-case for artificial intelligence is healthcare imaging. In this course, you will improve your machine learning skills by creating an algorithm for automatic liver segmentation. Code: https://github.com/amine0110/Liver-Segmentation-Using-Monai-and-PyTorch Course Contents: (0:00:00) Introduction (0:02:11) What is U-Net (0:13:21) Software Installation (0:22:35) […]

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AI

Machine Learning Databases and How to Access them with Pytorch – MNIST Tutorial

Here is a great tutorial about popular Machine Learning databases and how we can easily access them with Pytorch. In particular, we will focus on MNIST, which is a handwritten digits database with 70,000 different images. We will load it with a very simple Pytorch command and we will have a closer look at its […]

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AI Python

5 Ways to Increase Your Model Performance with PyTorch Profiler

Sabrina Smai shows us five ways to increase your model performance using PyTorch Profiler.

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AI Research

Introducing Retiarii: A deep learning exploratory-training framework on NNI

Traditional deep learning frameworks such as TensorFlow and PyTorch support training on a single deep neural network (DNN) model, which involves computing the weights iteratively for the DNN model. Designing a DNN model for a task remains an experimental science and is typically a practice of deep learning model exploration. Retrofitting such exploratory-training into the […]

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Developer

BlazorDay 2021

On my livestream today, I briefly mentioned that I was excited about the potential of Blazor for web development. Fortunately, The Blazor Day is the online event around Blazor technologies. It’s organized by organized by 3 MVPs and it looks awesome.

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Deep Learning

Convolutions in Deep Learning – Interactive Demo App

deeplizard explains the importance of convolutions in deep learning. In deep learning, convolution operations are the key components used in convolutional neural networks. A convolution operation maps an input to an output using a filter and a sliding window. Use the interactive demonstration below to gain a better understanding of this process. 

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Data Science Databricks

MLflow Integration with PyCaret and PyTorch

In this talk, hosted by Databricks, learn how to build reproducible AI models and workflows using PyTorch and MLflow that can be shared across your teams, with traceability and speed up collaboration for AI projects.

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