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Training a CNN from Scratch using Data Augmentation

Analytics Vidhya

Introduction My last blog discussed the “Training of a convolutional neural network from scratch using the custom dataset.” ” In that blog, I have explained: how to create a dataset directory, train, test and validation dataset splitting, and training from scratch. This blog is […].

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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Journey to AI blog

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. This blog post will clarify some of the ambiguity. Your AI must be explainable, fair and transparent.

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Understanding Graph Neural Network with hands-on example| Part-2

Becoming Human

Photo by Paulius Andriekus on Unsplash Welcome back to the next part of this Blog Series on Graph Neural Networks! The following section will provide a little introduction to PyTorch Geometric , and then we’ll use this library to construct our very own Graph Neural Network!

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#53 How Neural Networks Learn More Features Than Dimensions

Towards AI

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. They have written a blog post discussing the results and limitations of current RAG approaches. Check out the blog here and support a fellow community member.

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#53 How Neural Networks Learn More Features Than Dimensions

Towards AI

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. They have written a blog post discussing the results and limitations of current RAG approaches. Check out the blog here and support a fellow community member.

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Generative AI vs. predictive AI: What’s the difference?

IBM Journey to AI blog

Generative adversarial networks (GANs) consist of two neural networks: a generator that produces new content and a discriminator that evaluates the accuracy and quality of the generated content. Conversely, predictive AI estimates are more explainable because they’re grounded on numbers and statistics.

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NeRFs Explained: Goodbye Photogrammetry?

PyImageSearch

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?