Neural Oblivious Decision Ensembles(NODE) – A State-of-the-Art Deep Learning Algorithm for Tabular Data

Deep Learning brought about revolutions in many machine learning problems from the field of Computer Vision, Natural Language Processing, Reinforcement Learning, etc. But tabular data still remains firmly under classical machine learning algorithms, namely the gradient boosting algorithms(I have a whole series on different Gradient Boosting algorithms, if you are interested). Intuitively, this is strange, … Continue reading Neural Oblivious Decision Ensembles(NODE) – A State-of-the-Art Deep Learning Algorithm for Tabular Data

PyTorch Tabular – A Framework for Deep Learning for Tabular Data

It is common knowledge that Gradient Boosting models, more often than not, kick the asses of every other machine learning models when it comes to Tabular Data. I have written extensively about Gradient Boosting, the theory behind and covered the different implementations like XGBoost, LightGBM, CatBoost, NGBoost etc. in detail. The unreasonable effectiveness of Deep … Continue reading PyTorch Tabular – A Framework for Deep Learning for Tabular Data

How to Train and Deploy Custom AI-Generated Quotes using GPT2, FastAPI, and ReactJS

The Problem Good quotes help make us stronger. What is truly inspiring about quotes is not their tone or contentedness but how those who share them reflect life experiences that really serve others. I didn’t write the above quote about quotes(Quote-ception), but an AI model I trained did. And it says it better than I … Continue reading How to Train and Deploy Custom AI-Generated Quotes using GPT2, FastAPI, and ReactJS

Intermittent Demand Forecasting with Deep Renewal Processes

Let’s face it, anyone who has worked on Time Series Forecasting problems in the retail, logistics, e-commerce etc. would have definitely cursed that long tail which never behaves. The dreaded intermittent time series which makes the job of a forecaster difficult. This nuisance renders most of the standard forecasting techniques impractical, raises questions about the … Continue reading Intermittent Demand Forecasting with Deep Renewal Processes


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