Udemy – Feature Engineering for Machine Learning
English | Tutorial | Size: 3.03 GB
Learn imputation, variable encoding, discretization, feature extraction, how to work with datetime, outliers, and more. [Read more…]
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Udemy – Feature Engineering for Machine Learning
English | Tutorial | Size: 3.03 GB
Manning – Fighting Churn Churn Analysis Feature Engineering-iLLiTERATE
English | Tutorial | Size: 545.08 MB
Manning – Feature Mapping a Smooth Path From Collaboration to High-quality Executable Specifications-iLLiTERATE
English | Tutorial | Size: 102.86 MB
Animation Mentor – Course 6 – Feature Animation Acting & Polish
English | Size: 14.8GB
Category: Tutorial
In this final course, combine all the skills you’ve acquired and apply the concepts to a new animated shot. [Read more…]
Manning – Recommending Art With Feature Engineering-iLLiTERATE
English | Size: 2.58 GB
Category: Tutorial
Sinan Ozdemir teaches how to use core tenants of feature engineering to build your own art recommendation engine from scratch. [Read more…]
Red Barn Pictures – Creature Feature: 60 Years of the Gill-Man (2014)
English | Size: 1.41 GB
Category: Documentary
Documents the era surrounding the creation, marketing and distribution of the influential horror film, "Creature From the Black Lagoon," and the two sequels that followed. [Read more…]
PluralSight – Feature Engineering JUL2020-REBAR
English | Size: 1.59 GB
Category: Tutorial
Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering where we will discuss good vs bad features and how you can preprocess and transform them for optimal use in your models. [Read more…]
Linkedin Learning – Applied Machine Learning Feature Engineering Online Class-ZH
English | Size: 342.18 MB
Category: Tutorial
The quality of the predictions coming out of your machine learning model is a direct reflection of the data you feed it during training. Feature engineering helps you extract every last bit of value out of data. This course provides the tools to take a data set, tease out the signal, and throw out the noise in order to optimize your models. The concepts generalize to nearly any kind of machine learning algorithm. Instructor Derek Jedamski provides a refresher on machine learning basics and a thorough introduction to feature engineering. He explores continuous and categorical features and shows how to clean, normalize, and alter them. Learn how to address missing values, remove outliers transform data, create indicators, and convert features. In the final chapters, Derek explains how to prepare features for modeling and provides four variations for comparison, so you can evaluate the impact of cleaning, transforming, and creating features through the lens of model performance [Read more…]
Pluralsight – Feature Toggles Package Management and Versioning with Azure DevOps-ViGOROUS
English | Size: 175.68 MB
Category: Tutorial