Gain State-Of-The-Art Results on Tabular Data with Deep Learning & Embedding Layers [A How To Guide]

Written by michael-li | Published 2020/02/03
Tech Story Tags: artificial-intelligence | machine-learning | data-science | deep-learning | word-embeddings | hackernoon-top-story | ml-top-story | ai-top-story

TLDR Tree-based models like Random Forest and XGBoost have become very popular in solving tabular data problems. We’ll try to use fast.ai’s tabular module on the Blue Book Bulldozers Competition on Kaggle and see how far this approach can go. Deep Learning is more for unstructured data like image, audio or NLP, but embedding layers for categorical data changed this perspective. We'll use the deep Learning and Embedding Layers to solve tabular(structured) data problems in a Pandas DataFrame.via the TL;DR App
no story
Written by michael-li | | Product Manager | Machine Learning Practitioner | UI/UX Designer/Preacher | Full-Stack Developer |
Published by HackerNoon on 2020/02/03
ABOUTHow hackers start their afternoons. We publish tech stories and build publishing software.

READEntirely free library read by hundreds of millions to learn anything about any technology.

WRITEHackerNoon elevates quality technology writing far and wide across the interwebs.

PARTNERHackerNoon works directly with tech companies to place ads by content relevancy