I made two models for predicting reorder & None. Following are the features I made.
- How often the user reordered items
- Time between orders
- Time of day the user visits
- Whether the user ordered ...
Similar Articles (10 found)
π 59.7% similar
Max Lin on finishing second in the R Challenge
I participated in the R package recommendation engine competition on Kaggle for two reasons. First, I u...
π 57.0% similar
Quan Sun on finishing in second place in Predict Grant Applications
Iβm a PhD student of the Machine Learning Group in the University of Waikato, Hami...
π 54.3% similar
Writing an LLM from scratch, part 22 -- finally training our LLM!
This post wraps up my notes on chapter 5 of Sebastian Raschka's book "Build a Large ...
π 53.1% similar
Recommendation System
Perhaps the most famous recommender system is the so-called matrix factorization. In this collaborative recommender, users and i...
π 52.8% similar
Fast Python Collaborative Filtering for Implicit Datasets.
This project provides fast Python implementations of several different popular recommendati...
π 52.7% similar
The Kaggle Blueprints
Welcome to the first edition of a new article series called "The [Kaggle](https://www.kaggle.com/) Blueprints", where we will an...
π 51.9% similar
|
The data consists of a list of bid events (auction id, user id, time, IP, location) and a table, X, with the bidder id's, the hashed contact and pay...
π 51.7% similar
Introduction
Based on these two factors, Iβve decided to do an exploration of how different decision tree hyperparameters affect both the performance ...
π 50.9% similar
Why Classical Machine Learning Still Matters
In an era of GPU supremacy, why do real-world business cases depend so much on classical machine learning...
π 50.7% similar
2 Years of ML vs. 1 Month of Prompting
November 7, 2025
Recalls at major automakers cost hundreds of millions of dollars a year. Itβs a huge issue. To...