Automated Machine Learning Hands on AutoML for beginners

Automated Machine Learning Hands on AutoML for beginners, available at $64.99, has an average rating of 4.55, with 18 lectures, based on 23 reviews, and has 287 subscribers.

You will learn about 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 This course is ideal for individuals who are You want to get an overview over automl or You want to use automl for free or hands on code example on how to apply those libraries on demo datasets or This course is NOT A basic introduction to what is ML/DL or an introduction to python or This course is NOT a data science theory course or This course is NOT an in-depth dive into each hyperparameter which can be adjusted / tuned It is particularly useful for You want to get an overview over automl or You want to use automl for free or hands on code example on how to apply those libraries on demo datasets or This course is NOT A basic introduction to what is ML/DL or an introduction to python or This course is NOT a data science theory course or This course is NOT an in-depth dive into each hyperparameter which can be adjusted / tuned.

Enroll now: Automated Machine Learning Hands on AutoML for beginners

Summary

Title: Automated Machine Learning Hands on AutoML for beginners

Price: $64.99

Average Rating: 4.55

Number of Lectures: 18

Number of Published Lectures: 18

Number of Curriculum Items: 18

Number of Published Curriculum Objects: 18

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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

Target Audiences

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

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

Course Curriculum

Chapter 1: AutoML Introduction Hands on!

Lecture 1: Resources

Lecture 2: 2 AutoML hands on for beginners intro

Lecture 3: Important note

Lecture 4: 3 Auto EDA

Lecture 5: 4 The 1st AutoML Library Regression example

Lecture 6: 5 The 1st AutoML Library Classification example

Lecture 7: 6 The 2nd AutoML Library Regression example

Lecture 8: 7 The 2nd AutoML Library Classification example

Lecture 9: Important note

Lecture 10: 8 The 3rd AutoML Library Regression example

Lecture 11: 9 The 3rd AutoML Library Classification example

Lecture 12: 10 The 4th AutoML Library Regression example

Lecture 13: 11 The 4th AutoML Library Classification example

Lecture 14: 12 The 5th AutoML Library Regression example

Lecture 15: 13 The 5th AutoML Library Classification example

Lecture 16: 14 The 6th AutoMLLibrary Regression example

Lecture 17: 15 The 6th AutoML Library Classification example

Chapter 2: Bonus

Lecture 1: Learn more AI

Instructors

Dan We
Coach

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 5 votes
5 stars: 17 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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