Predicting job salaries from ads - a Kaggle competition

Overview

Predicting advertised salaries

See http://fastml.com/predicting-advertised-salaries/ for description.

2vw.py - convert a combined train+test file to VW format
2vw_loc.py - the same, but for data transformed with update_locations.py
add_dummy_salaries.py - add dummy salaries columns (2) to a test file; drop headers
first.py - Take some lines from the input file and save them to the output file
split.py - split a file into two randomly, line by line
unlog_predictions.r - convert VW's log predictions back to a normal scale by taking exp()
update_locations.py - replace location columns from the original file with parsed location (five columns) - slightly buggy
update_locations_fixed.py - a fixed version of update_locations.py
Owner
Zygmunt Zając
I should have learned to play the guitar / I should have learned to play them drums
Zygmunt Zając
K-Means clusternig example with Python and Scikit-learn

Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se

Emin 1 Dec 13, 2021
Time Series Prediction with tf.contrib.timeseries

TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input

Zhiyuan He 476 Nov 17, 2022
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning

📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2

Claudia dos Anjos 1 Jan 05, 2022
Simple data balancing baselines for worst-group-accuracy benchmarks.

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

Facebook Research 29 Dec 02, 2022
ML Kaggle Titanic Problem using LogisticRegrission

-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c

Mahmoud Nasser Abdulhamed 3 Oct 23, 2022
hgboost - Hyperoptimized Gradient Boosting

hgboost is short for Hyperoptimized Gradient Boosting and is a python package for hyperparameter optimization for xgboost, catboost and lightboost using cross-validation, and evaluating the results o

Erdogan Taskesen 34 Jan 03, 2023
fastFM: A Library for Factorization Machines

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

1k Dec 24, 2022
Simple, light-weight config handling through python data classes with to/from JSON serialization/deserialization.

Simple but maybe too simple config management through python data classes. We use it for machine learning.

Eren Gölge 67 Nov 29, 2022
Markov bot - A Writing bot based on Markov Chain for Data Structure Lab

基于马尔可夫链的写作机器人 前端 用html/css完成 Demo展示(已给出文本的相应展示) 用户提供相关的语料库后训练的成果 后端 要完成的几个接口 解析文

DysprosiumDy 9 May 05, 2022
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Benedek Rozemberczki 1.8k Jan 03, 2023
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

Chao Ma 3k Jan 08, 2023
A classification model capable of accurately predicting the price of secondhand cars

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this

Akarsh Singh 2 Sep 13, 2022
Scikit-Garden or skgarden is a garden for Scikit-Learn compatible decision trees and forests.

Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.

260 Dec 21, 2022
End to End toy example of MLOps

churn_model MLOps Toy Example End to End You might find below links useful Connect VSCode to Git MLFlow Port Heroku App Project Organization ├── LICEN

Ashish Tele 6 Feb 06, 2022
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Augusto Almeida 84 Nov 25, 2022
Machine Learning from Scratch

Machine Learning from Scratch Author: Shengxuan Wang From: Oregon State University Content: Building Machine Learning model from Scratch, without usin

ShawnWang 0 Jul 05, 2022
Hierarchical Time Series Forecasting using Prophet

htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th

Collin Rooney 131 Dec 02, 2022
GroundSeg Clustering Optimized Kdtree

ground seg and clustering based on kitti velodyne data, and a additional optimized kdtree for knn and radius nn search

2 Dec 02, 2021
A simple python program which predicts the success of a movie based on it's type, actor, actress and director

Movie-Success-Prediction A simple python program which predicts the success of a movie based on it's type, actor, actress and director. The program us

Mahalinga Prasad R N 1 Dec 17, 2021
Evidently helps analyze machine learning models during validation or production monitoring

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Current

Evidently AI 3.1k Jan 07, 2023