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Implementing Batch Normalization with NumPy

Batch normalization is a recent idea introduced by Ioffe et al, 2015. It allows us to use much higher learning rates and be less careful about initialization.

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Image-to-Recipe Translation with Deep Convolutional Neural Networks

We present a novel retrieval-based approach for recipe prediction using a re-ranking scheme.

Sep 09 2018 · 13 min read

Generative Adversarial Networks (GAN) in TensorFlow

Estimating generative models via an adversarial process in TensorFlow...
Feb 20 2019 · 14 min read

Optimization Tricks for Jupyter Notebooks

Find bottlenecks and increase pythons speed performance by magnitudes...
Jan 01 2019 · 11 min read

Implementing Long short-term memory (LSTM) with NumPy

Learn how to implement a forward pass and backpropagation by hand...
Jan 12 2019 · 10 min read

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All Thoughts

Convolutional Models in TensorFlow

Gain an intuition about convolutions and understand different steps used in convolutional neural network architectures.

Jun 16 2019 · 8 min read

Generative Adversarial Networks (GAN) in TensorFlow

Estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a discriminative model D.

Feb 20 2019 · 9 min read

Implementing Long short-term memory (LSTM) with NumPy

Learn how to implement a forward pass and backpropagation by hand...

Jan 12 2019 · 10 min read

Optimization Tricks for Jupyter Notebooks

Find bottlenecks and increase pythons speed performance by magnitudes...

Jan 01 2019 · 11 min read

Implementing Batch Normalization with NumPy

Batch normalization is a recent idea introduced by Ioffe et al, 2015. It allows us to use much higher learning rates and be less careful about initialization.

Dec 20 2018 · 11 min read

Image-to-Recipe Translation with Deep Convolutional Neural Networks

We present a novel retrieval-based approach for recipe prediction using a re-ranking scheme.

Sep 09 2018 · 13 min read
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