#Xgboost

evaluator of parse

evalparse

Another reason why Julia is the Data Science language of the (near) future:I have been trying to make JLBoost.jl (a pure-#julialang) XGBoost-like) "hackable".Background: XGBoost has a grow_policy parameter with two

Arnab Biswas

arnabbiswas1

Few things which I found interesting from Keynote interview of @faisalzs by @samcharrington at #twimlcon 2021 day 2.https://twitter.com/twimlai/status/1351948281635504129 3 types of users of ML platform- Algorithm Engineers: SW Engineering

Shreya Shankar

sh_reya

My thoughts on baselines, a concept that is *extremely* relevant in industry ML but does not exactly translate from academic ML: 1/9 In academic ML projects, my classmates and I

Neal Jean

nealjean1

Idea from machine learning applied to startupsRepeat founders are like linear models, first-time founders are like deep learning In ML, inductive bias is what lets a model generalize beyond training

Full Stack Deep Learning

full_stack_dl

1/ Our latest Production ML meetup features Erik Reppel (@programmer -- that handle tho ), a Sr ML Platform Engineer at Coinbase. We covered building reproducible / performant ML pipelines,

Edward Raff

EdwardRaffML

An extension of my NeurIPS work accepted to @RealAAAI #AAAI2021 "Research Reproducibility as a Survival Analysis" is now online! paper https://arxiv.org/abs/2012.09932 code https://github.com/EdwardRaff/Research-Reproducibil

The Breakout

BreakoutDynasty

NFL WR Edition: Have you ever wondered what it would be like to stick a bunch of WR data into a machine learning model?We'll walk through how we created the

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