• Skip to main content
  • Skip to primary sidebar

PyQuant News

Resources for developers using Python for scientific computing and quantitative analysis

You are here: Home / Archives for Feature Engineering
Latest Resources in Feature Engineering

Feature Engineering

The Data Training/Test Split: Are You Doing it Right? loominus.ai

Published August 17, 2019 under Data Science

One of the most common mistakes data scientists make when training machine learning models is incorrectly splitting data for training and testing. The train/test split involves splitting data during the model training and evaluation process.

Learner makes this simple with a single parameter selection during the model building process. It’s also simple to set the percentage split between training and testing data for each model trained. 

Feature Engineering, Machine Learning

Building data pipelines with Teraport for feature engineering loominus.ai

Published August 3, 2019 under Data Science

Data pipelines are where most of the time is spent for those working with data because the bulk of a machine learning project involves data collection and cleaning. Loominus gives everyone the power to build the data pipelines critical to any machine learning project. 

Teraport is a powerful tool within the Loominus product suite that ingests and stages data. In another post, we’ll discuss the data ingestion APIs. For now we’ll focus on building a powerful data pipeline for feature engineering.

Feature Engineering, Machine Learning

Using featuretools in Python for Classification medium.com

Published September 7, 2018 under Data Science

Feature Engineering, featuretools, Machine Learning

A Feature Selection Tool for Machine Learning in Python towardsdatascience.com

Published July 4, 2018 under Machine Learning

Feature Engineering, Python

PointCNN – A simple and general framework for feature learning from point cloud yangyanli.github.io

Published January 30, 2018 under Machine Learning

Feature Engineering, Python

Featuretools: Automated feature engineering for Python github.com

Published January 23, 2018 under Machine Learning

Feature Engineering, Python

Primary Sidebar

Welcome to PyQuant News

PyQuant News algorithmically curates the best resources from around the web for developers using Python for scientific computing and quantitative analysis.

PyQuant Books

  • Software Architecture with PythonSoftware Architecture with Python

Categories

  • Blogs (9)
  • Books (20)
  • Computer Vision (22)
  • Data Science (147)
  • Education (5)
  • Investing (7)
  • Machine Learning (157)
  • Neural Networks (13)
  • Programming (14)
  • Python (296)
  • Quant Finance (49)
  • Statistics (3)
  • Trading (48)
  • Web Development (6)

Archives

  • March 2021 (3)
  • February 2021 (3)
  • January 2021 (7)
  • November 2020 (1)
  • October 2020 (7)
  • September 2020 (4)
  • August 2020 (1)
  • July 2020 (4)
  • May 2020 (7)
  • April 2020 (2)
  • March 2020 (1)
  • February 2020 (2)
  • January 2020 (5)
  • December 2019 (6)
  • November 2019 (10)
  • October 2019 (9)
  • September 2019 (9)
  • August 2019 (17)
  • July 2019 (14)
  • June 2019 (10)
  • May 2019 (5)
  • April 2019 (19)
  • March 2019 (9)
  • February 2019 (7)
  • January 2019 (5)
  • December 2018 (19)
  • November 2018 (5)
  • October 2018 (3)
  • September 2018 (17)
  • August 2018 (11)
  • July 2018 (15)
  • June 2018 (24)
  • May 2018 (5)
  • April 2018 (4)
  • March 2018 (3)
  • February 2018 (5)
  • January 2018 (79)
  • December 2017 (13)
  • November 2017 (23)
  • October 2017 (20)
  • September 2017 (8)
  • August 2017 (17)
  • July 2017 (15)
  • June 2017 (11)
  • May 2017 (13)
  • April 2017 (11)
  • March 2017 (11)
  • February 2017 (7)
  • January 2017 (21)
  • December 2016 (7)
  • October 2016 (4)
  • September 2016 (3)
  • August 2016 (4)
  • July 2016 (8)
  • June 2016 (6)
  • April 2016 (12)
  • March 2016 (2)
  • February 2016 (2)
  • January 2016 (8)
  • November 2015 (2)
  • October 2015 (5)
  • September 2015 (8)
  • August 2015 (11)
  • July 2015 (13)
  • June 2015 (51)
  • May 2015 (84)
  • April 2015 (39)