Automated Machine Learning - Auto ML, TPOT, H2O, Auto Keras (Learn Various Automated ML Techniques)

This course is designed to teach you Automated Machine Learning (AutoML). You'll explore powerful tools like TPOT, AutoML, AutoKeras, and H2O, which help streamline the process of building and optimizing machine learning models. With a basic understanding of Python and Sklearn, you'll be ready to dive into the course and enhance your data science skills.

You'll engage in five hands-on exercises illustrating AutoML techniques' power. These include detecting credit card fraud using AutoML, classifying handwritten digits with AutoKeras on the MNIST dataset, predicting insurance outcomes with TPOT, identifying potential customer churn using H2O, and forecasting sales with H2O. Each exercise of the course "Automated Machine Learning - Auto ML, TPOT, H2O, Auto Keras" is designed to show you how these tools can automatically find the best models and configurations for your data.

Whether you're a professional data scientist looking to save time and improve efficiency or a newcomer wanting to learn about the latest advancements in machine learning, this course offers valuable insights and practical skills. By the end of this course, "Automated Machine Learning - Auto ML, TPOT, H2O, Auto Keras", you'll have a solid understanding of how to use AutoML tools to solve real-world problems and optimize your machine learning workflows.

Automated Machine Learning - Auto ML, TPOT, H2O, Auto Keras Table of Contents:

1. Introduction to AutoML - 04:16
2. Load Dataset - 01:55
3. Visualize the Dataset - Perform Distribution Plot on Fraud Data - 05:24
4. Scale Data using RobustScaler - 01:57
5. Remove Data Outliers - 09:36
6. Ensemble and AutoML Predictions - 07:34
7. Introduction to AutoKeras - 09:59
8. Implementing AutoKeras on MNIST Dataset - 04:14
9. AutoKeras using StructuredDataRegressor Part 1 - 03:06
10. AutoKeras using StructuredDataRegressor Part 2 - 03:45
11. TPOT Introduction - 06:40
12. TPOT Classifier - 05:02
13. Insurance Predictions using TPOT - 04:38
14. Visualize Data - 06:17
15. Ensemble Model Predictions - 07:54
16. TPOT Regressor - 04:15
17. Stacked Model - 05:00
18. Introduction to H2O - 08:15
19. Introduction to Churn Prediction using H2O - 02:01
20. Train the Dataset - 04:20
21. H2O Leaderboard and Model Performance - 03:46
22. Making Predictions - 02:47
23. Introduction to Sales Prediction using H2O - 02:56
24. Preprocessing the Dataset - 05:02
25. Training and Predictions using Decision Trees - 03:42
26. Training and Making Predictions using H2O - 03:53

Who is this course for?

1. Beginner Programmer Enthusiast Aspiring to Become a Data Scientist
2. New to Automated Machine Learning Fundamentals

Click on the links below to Download Automated Machine Learning - Auto ML, TPOT, H2O, Auto Keras!