Another exquisit release
Lynda.Applied.Machine.Learning.Foundations-XQZT
Title: Applied Machine Learning: Foundations
Publisher: Lynda
Size: 379M (396572345 B)
Files: 8F
Date: 05/10/2019
Course #: 751335
Type: Big Data
Published: 5/10/2019
Modified: N/A
URL: www.lynda.com/Python-tutorials/Applied-Machine-Learning-Foundations/751335-2.html
Author: Derek Jedamski
Duration: 2h 38m
Skill: Beginner
Exer/Code: [X]
Installation:
Unpack that shit, run that shit
Notes:
Anyone who can write basic Python is capable of fitting a simple
machine learning model on a clean dataset. The competitive edge
comes in the ability to customize and optimize those models for
specific problems. The workflow used to build effective machine
learning models and the methods used to optimize those models are
typically not algorithm or problem specific. In this course, the
first installment in the two-part Applied Machine Learning
series, instructor Derek Jedamski digs into the foundations of
machine learning, from exploratory data analysis to
evaluating a model to ensure it generalizes to unseen
examples. Instead of zeroing in on any specific machine
learning algorithm, Derek focuses on giving you the tools to
efficiently solve nearly any kind of machine learning problem.