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Automated Machine Learning Hands on AutoML for beginners

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MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 15 lectures (2h 26m) | Size: 791.8 MB

How to use AutoML in python AutoML in practise What is Automated Machine Learning


What you’ll learn:
A hands on overview of free python automl packages and how to use them
What is automl
How to use automl in python
Automated machine learning in practise

Requirements
We only use free AutoML libraries
Python knowledge is helpful – this is not a “learning python” class
AutoML requires us to write some python code but not a lot

Description
What is Automated Machine Learning (AutoML)

Will Automated Machine Learning replace Datascientists?

How to use AutoML in python

What AutoML options are available and free to use?

If you are a beginner and want answers to those questions and try AutoML yourself then this course is for you.

Here we go through various AutomatedMachine Learning (and Deep Learning) frameworks which are currently available (not an extensive list of course there are many more).

The main goal is to get an overview of what AutoML is and how to use it in python. We focus on free AutoML libraries instead of commercial ones so that you can follow along and try them yourself. The course has demo datasets for regression as well as a classification task so we see both supervised learning tasks for each AutoML libary we are going to cover.

Feel free to try out Automated Machine Learning with your own data as well

For this course you should have used Python before (Even AutoML requires us to write a tiny little bit of code)

Please also understand what this course is not

This course does not offer:

A basic introduction to what is ML/DL or an introduction to python

An in-depth theoretic dive into each hyperparameter which can be adjusted / tuned

An all-in-one solution for every project you want to take in the future

This course does offer:

hands on code examples on how to apply those libraries on demo datasets

Specific relevant information for each library you need to be aware of when you use it

Helpful tools for any data scientist of business person who wants to reduce redundant and repetitive tasks and free some time to focus on the main steps in the data science life cyclle

Who this course is for
You want to get an overview over automl
You want to use automl for free
hands on code example on how to apply those libraries on demo datasets
This course is NOT A basic introduction to what is ML/DL or an introduction to python
This course is NOT a data science theory course
This course is NOT an in-depth dive into each hyperparameter which can be adjusted / tuned


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