Categories neural-networks

49 posts

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AI for Dinosaurs

Knowing a little about everything is often better than having one expert skill. This is particularly true for people entering the debate in emerging markets. Most notably, tech. Most folks think they know a little about AI. But the field is so new and growing so fast that the current experts […]

Understanding Few-shot intelligence as a Meta-Learning Problem

Meta learning is learning to learn. Usually applied for hyperparameter tuning, recent applications have started focussing on few-shot learning. Before we explore two novel techniques to achieve this, lets understand some key aspects of the problem. As a guiding example, we will focus on our ability to grasp new words […]

Only Numpy: Decoupled Convolutional LSTM to classify Puppy GIFs and Baby GIFs with Interactive…

Only Numpy: Decoupled Convolutional LSTM to classify Puppy GIFs and Baby GIFs with Interactive Code. Before reading on, please note that this is experimental model, I just wanted to challenge myself to build this model. So there are some high possibilities that there are some errors in the back propagation […]

The Who’s Who Of Machine Learning, And Why You Should Know Them

If you are a machine learning enthusiast , or even planing on getting into the field soon. THIS IS YOUR TIME. Why you ask? Take any aspect of AI that’s been gaining momentum lately. The guy who MADE the algorithm is probably doing research on it somewhere in silicon valley right now. Needless […]

Deep Learning with Python

The human brain imitation. The main reason behind deep learning is the idea that, artificial intelligence should draw inspiration from the brain. This perspective gave rise to the “Neural Network” terminology. The brain contains billions of neurons with tens of thousands of connections between them. Deep learning algorithms resemble the […]

Building a Deep Neural Net In Google Sheets

I want to show you that Deep Convolutional Neural Nets are not nearly as intimidating as they sound. And I’ll prove it by showing you an implementation of one that I made in Google Sheets. It’s available here. Copy it (use the File → Make a copy option in top […]

Only Numpy: Implementing Simple ResNet ( Deep Networks with Stochastic Depth) for MNIST…

Only Numpy: Implementing Simple ResNet ( Deep Networks with Stochastic Depth) for MNIST Classification with Interactive Code Image from Pixel Bay So I was reading this article “Stochastic Depth Networks will Become the New Normal” and there I saw the paper “Deep Networks with Stochastic Depth”. Upon reading that paper I […]

Deep Gray Matter (DGM) Segmentation using 3D Convolutional Neural Network: application to QSM (Part…

Deep Gray Matter (DGM) Segmentation using 3D Convolutional Neural Network: application to QSM (Part 1) [Update 2018–02–04]: new results can be found at Part 2. Code Available at Github: https://github.com/zl376/segDGM_CNN Motivation Automated segmentation by computered is desired and indeed widely studied in MRI analysis. Specifically, for QSM (Quantitative Susceptibility Mapping), an MRI […]

My First Step Into Machine Learning

A guide to anyone who wants to learn machine learning from scratch, based on my experiences. The fashion MNIST data set on kaggle A few months back is when i started hearing a lot about machine learning and ai, I thought it was something that only M-Tech students and researchers dealt […]

Only Numpy: Implementing Mini VGG (VGG 7) and SoftMax Layer with Interactive Code

Picture from Pixel Bay I wanted to practice my Back Propagation skills on Convolutional Neural Network. And I wanted to implement my own VGG net (from original paper “Very Deep Convolutional Networks for Large-Scale Image Recognition”) for sometime now, so today I decided to combine those two needs. If you are not […]