Feb 10, 2020
kNN classification using Neighbourhood Components Analysis
A detailed explanation of Neighbourhood Components Analysis with a GPU-accelerated implementation in PyTorch.
Oct 31, 2019
Learning to Assemble and to Generalize from Self-Supervised Disassembly
Excited to finally share what I've been up to this summer at Google!
Nov 5, 2018
Dex-Net 2.0: Deep Learning to Plan Robust Grasps
A detailed read-through of Dex-Net 2.0.
Sep 28, 2018
Learning What to Learn and When to Learn It
Can Deep Neural Networks learn more efficiently?
Aug 13, 2017
Getting Up and Running with PyTorch on Amazon Cloud
Installing PyTorch on a GPU-powered AWS instance with $150 worth of free credits.
Jul 20, 2017
Understanding Recurrent Neural Networks - Part I
I'll introduce the motivation and intuition behind RNNs, explaining how they capture memory and why they're useful for working with sequences.
Jan 18, 2017
Deep Learning Paper Implementations: Spatial Transformer Networks - Part II
In part II, we cover the Spatial Transformer module and summarize its paper in detail.
Jan 10, 2017
Deep Learning Paper Implementations: Spatial Transformer Networks - Part I
Part I covers affine image transformations and bilinear interpolation.
Sep 26, 2016
Nuts and Bolts of Applying Deep Learning
A summary of Andrew Ng's talk at the 2016 Bay Area Deep Learning School
Sep 14, 2016
Deriving the Gradient for the Backward Pass of Batch Normalization
I'll work out an expression for the gradient of the batch norm layer in detailed steps and provide example code.
Jul 13, 2016
A Complete Guide to K-Nearest-Neighbors with Applications in Python and R
I'll introduce the intuition and math behind kNN, cover a real-life example, and explore the inner-workings of the algorithm by implementing the code from scratch.