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The One Thing You Need To Truly Understand Neural Networks is to Understand …
Author(s): Nandini Tengli Originally published on Towards AI. Neural Networks can learn almost anything. From learning to differentiate between Dogs and Cats to learning to be THE go-to chatbot for 100s of millions of people. Neural Networks seem like magic. What if …
Towards 3D Deep Learning: Artificial Neural Networks with Python
Author(s): Florent Poux, Ph.D. Originally published on Towards AI. A Hands-on Beginner's Guide to Unlock the Power of Artificial Neural Networks in Python This member-only story is on us. Upgrade to access all of Medium. Artificial Neural Networks Applications for Raster, Vector …
PyTorch LSTM — Shapes of Input, Hidden State, Cell State And Output
Author(s): Sujeeth Kumaravel Originally published on Towards AI. In Pytorch, to use an LSTM (with nn.LSTM()), we need to understand how the tensors representing the input time series, hidden state vector and cell state vector should be shaped. In this article, let …
Knowledge Distillation in Modern AI: Bridging the Gap between Powerful and Compact Models
Author(s): Shahriar Hossain Originally published on Towards AI. 1. Space Exploration This member-only story is on us. Upgrade to access all of Medium. In the ever-evolving landscape of artificial intelligence, as models burgeon in complexity and size, the challenge arises: How do …
How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?
Author(s): AlishaS Originally published on Towards AI. Machine Learning vs. AI vs. Deep Learning vs. Neural Networks: What’s the Difference? The rapid evolution of technology is molding our everyday existence as businesses turn more and more to sophisticated algorithms for efficiency. Amidst …
GANs (Generative Adversarial Networks:)
Author(s): Data Science meets Cyber Security Originally published on Towards AI. We Saw the Generative AI, Now Let’s See How Actually It Is Generated.! IMAGE SOURCE: BY AUTHOR INTRODUCTION: GANs, Generative Adversarial networks, let’s first understand what GANs are. So I have …
Graph Attention Networks Paper Explained With Illustration and PyTorch Implementation
Author(s): Ebrahim Pichka Originally published on Towards AI. A detailed and illustrated walkthrough of the “Graph Attention Networks” paper by Veličković et al. with the PyTorch implementation of the proposed model. Illustration of the message-passing layer in a Graph Attention Network s— …
1Cycle Learning Rate Scheduling with TensorFlow and Keras
Author(s): Jonathan Quijas Originally published on Towards AI. Machine Learning Engineering A Practical Methodology to Set the Most Important Hyperparameter in Deep Learning Photo by David Everett Strickler on Unsplash Problem Statement Training a Deep Neural Network can be a challenging task. …
Why Tensorflow is a great choice for building projects powered by Computer Vision
Author(s): Nour Islam Mokhtari Originally published on Towards AI. Explained by an AI engineer who works on Computer Vision applications Join hundreds of subscribers to my weekly newsletter if you’re interested in learning and staying up-to-date with what’s happening in the field …
Let’s Learn: Neural Nets #3 — Activation Functions
Author(s): Bradley Stephen Shaw Originally published on Towards AI. A beginner’s guide to activation functions in neural nets. Photo by Antoine Dautry on Unsplash Today we’ll be looking at activation functions in neural nets — the who, what, where, and why of …
How to Train MAML(Model-Agnostic Meta-Learning)
Author(s): Sherwin Chen Originally published on Towards AI. An elaborate explanation for MAML and more Top highlight Source: Pixabay Model-Agnostic Meta-Learning(MAML) has been growing more and more popular in the field of meta-learning since it’s first introduced by Finn et al. in …
Stop Calling Automation AI… and the Natural Progression of Intelligent Machines
Author(s): Junis Alico Originally published on Towards AI. Defining Automation and AI | Towards AI Photo credit: Image by Gerd Altmann In the last few years, I’ve noticed a lot of C-level executives use AI in their keynote speeches and television appearances. …
DNC: Differential Neural Network
Author(s): Sherwin Chen Originally published on Towards AI. A detailed walk-through of DNC Photo by Philipp Katzenberger on Unsplash In the previous article, we discussed Neural Turing Machines(NTMs), which introduced an external memory to maintain information for later retrieval. In this post, …
A Surefire Way to Building a Neural Network Using Python
Author(s): Abhishek Kumar Originally published on Towards AI. Do you ever wonder how the browse feeds of your Netflix, YouTube, or Instagram Accounts can be so riveting so as to kill hours of your time against your will? Or how there are …
Why Perceptron Neurons Need Bias Input?
Author(s): Caio Davi Originally published on Towards AI. How to avoid bias input in Neural Networks? Please, just don’t. Everybody knows what is the neural network bias input. And everybody uses it since the very first Perceptron implementation. But why we use …
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