Convolutional Neural Network: How is it different from the other networks? What’s so unique about CNNs and what does convolution really do? This is a math-free introduction to the wonders of CNNs.
I am not a deep learning researcher, but I’ve come to know a few things about neural networks through various exposures. I’ve always heard that CNN is a type of neural network that’s particularly good at image-related problems. But, what does that really mean? What’s with the word “convolutional”? What’s so unusual about an image-related problem that a different network is required?
Recently I had the opportunity to work on a COVID-19 image classification problem and built a CNN-based classifier using
tensorflow.keras that achieved an 85% accuracy rate. Finally, I think I’ve figured out the answers to those questions. Let me share with you those answers in a math-free way. If you are already familiar with CNNs, this post should feel like a good refresher. If not, take a look, you could gain an intuitive understanding of the motivation behind CNNs and the unique features that define a CNN.
Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
The past few decades have witnessed a massive boom in the penetration as well as the power of computation, and amidst this information.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
Artificial Neural Networks — Recurrent Neural Networks. Remembering the history and predicting the future with neural networks. A intuition behind Recurrent neural networks.
In this video, Deep Learning Tutorial with Python | Machine Learning with Neural Networks Explained, Frank Kane helps de-mystify the world of deep learning and artificial neural networks with Python!