Hello Reader, Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below โ |
How do you generate images from low dimensional vectors?
How do you go from low dimensional data (like a vector of size 100) to higher dimensional data (like an image of size 200x200)?
In many Generative AI applications, youโd need to do this. So how can you do it?
In 2D, you have 2 options:
Whatโs the difference between the two options?
When you use Conv2DTranspose, youโre doing upsampling by adding zeros vertically and horizontally.
When you use UpSampling2D + Conv2D, youโre doing upsampling by duplicating rows and columns.
When to use which?
There is no one answer. It really depends on your experimentation.
One drawback though for Conv2DTranspose, is that sometimes the output generated image can have some checkerboard artifacts like the image below.
A recurrent problem with conda and how to solve it!
Most of us in the field of machine learning are using conda. But most of us face this problem at some point.
How do you create virtual environments on your local disk in a directory other than the default "Anaconda3/envs"?
Since we usually end up installing Anaconda in the default path during the installation process, it ends up being installed in the C drive.
This can quickly fill up the C disk.
So if you decide to create virtual environments and save them in another drive, how can you do that?
Well, you can achieve this by using the argument --๐ฉ๐ซ๐๐๐ข๐ฑ.
To install a new virtual environment in a directory inside D drive for example, you can do this:
๐๐จ๐ง๐๐ ๐๐ซ๐๐๐ญ๐ --๐ฉ๐ซ๐๐๐ข๐ฑ=๐:\๐ฉ๐๐ญ๐ก\...\๐ฒ๐จ๐ฎ๐ซ๐๐ง๐ฏ๐๐๐ฆ๐ ๐ฉ๐ฒ๐ญ๐ก๐จ๐ง=๐ฑ.๐ฑ
One thing you should know is, conda only keeps track of the environments included in the folder envs inside the anaconda folder.
So, the next time you need to activate your new virtual environment, move to the folder where you created it and activate it with:
๐๐จ๐ง๐๐ ๐๐๐ญ๐ข๐ฏ๐๐ญ๐ ๐ฒ๐จ๐ฎ๐ซ๐๐ง๐ฏ๐๐๐ฆ๐
ChatGPT is now available on Azure!
March 9th 2023
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๐ Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | ๐ก The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
Hello Reader, Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below โ AI Scribes: Transforming Medical Documentation Web Application for Medical Note Generation AI-powered medical scribes are revolutionizing clinical workflows by automating...
Hello Reader, Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below โ DeepSeek: A New Player in AI for Healthcare The new open-source LLM, DeepSeek, is creating buzz for its potential to transform AI in medicine and healthcare. Designed for...
Hello Reader, Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below โ Now You Can Use Large Language Models that are HIPAA Compliant People are finding ways to use large language models in all fields. MedTech is no exception. The amount of work...