The blog covers machine learning and deep learning: hands-on tutorials, package overviews, competition write-ups and findings from applied data science projects.

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  Layer-Wise Learning Rate in PyTorch

  Implementing discriminative learning rate across model layers

  Mar 29, 2022 · 8 min read

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  Estimating Text Readability with Transformers

  Interactive web app for predicting reading complexity of custom texts

  Nov 21, 2021 · 7 min read

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  Test-Time Augmentation for Tabular Data

  Improving predictive performance during inference

  Sep 8, 2021 · 12 min read

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  Extracting Intermediate Layer Outputs in PyTorch

  Simple way to extract activations from deep networks with hooks

  May 27, 2021 · 8 min read

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  Tracking ML Experiments with Neptune.ai

  Switching from spreadsheets to Neptune to improve model building

  Apr 30, 2021 · 11 min read

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  Computing Mean & STD in Image Dataset

  How to get channel-speicific mean and std in PyTorch

  Mar 8, 2021 · 6 min read

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  Gradient Accumulation in PyTorch

  Increasing batch size to overcome memory constraints

  Feb 19, 2021 · 4 min read

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  Training PyTorch Models on TPU

  Tutorial on using PyTorch/XLA 1.7 with TPUs

  Oct 30, 2020 · 15 min read

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  Pre-Training with Surrogate Labels

  Using the test sample to improve CNN performance

  Aug 30, 2020 · 14 min read

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  Profit-Driven Demand Forecasting

  Data Mining Cup 2020 solution with graident boosted trees

  Jul 27, 2020 · 31 min read

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  Detecting Blindness with Deep Learning

  Using CNNs to detect diabetic retinopathy in retina photos

  Jul 11, 2020 · 36 min read

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  Algorithmic Fairness in R

  Tutorial on using the fairness R package

  May 1, 2020 · 16 min read