### Neural Network Loss Visualization

Plotting its shape helps in understanding the properties and behaviour of a function. Unfortunately since we live in a 3D world, we can’t visualize functions […]

Plotting its shape helps in understanding the properties and behaviour of a function. Unfortunately since we live in a 3D world, we can’t visualize functions […]

So you developed a cool AI algorithm and want to show it off through a web service? You know a lot about AI algorithms and […]

If you follow the hardware for deep learning space, you may have heard of the term “systolic array”. A 2D systolic array forms the heart […]

The purpose of this post is to discuss my current understanding of roofline charts. Let me lay some background first. Before I got into machine […]

Over the past few days, I have been investigating how SSD (Single Shot Detector), an object detector introduced in the following paper in Dec 2016 […]

The purpose of this post is to provide math proofs and clarify some implementation details in the recently introduced reinforcement learning method called “Trust Region […]

You may have noticed that weights for convolutional and fully connected layers in a deep neural network (DNN) are initialized in a specific way. For […]

In this post, I’ll describe in detail how R-CNN (Regions with CNN features), a recently introduced deep learning based object detection and classification method works. R-CNN’s […]

In this post, I’ll describe some experiments on word2vec, a technique invented by researchers at Google that aims to find compact vector representations for words […]

In this post, I’ll show how to modify the spiral data set example presented in Karpathy’s post (http://cs231n.github.io/neural-networks-case-study/) to run in a data parallel mode. […]

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