neural networks for autoencoders and recommender systems

How to build autoencoders and recommender systems with neural networks. Machine learning hands on data science class

What you'll learn:

• You know what autoencoders can do
• You can create autoencoders in keras
• You can create a neural network recommender system
• You improve your knowledge about machine learning and AI using autoencoders and recommender systems
• You increase your knowledge and understanding of the deep learning library keras and pyhton
• You might open up new career opportunities for you which are not only highly rewarding but also offer more job satisfaction

Let's dive into data science with python and learn how to build recommender systems and autoencoders in keras

machine learning / ai ?How to learn machine learning in python? What are autoencoders? How to build a neural network recommender system with keras in python?

Good questions here is a point to start searching for answers

In the world of today and especially tomorrowmachine learning and artificial intelligence will be the driving force of the economy. Data science No matter who you are, an entrepreneur or an employee, and in which industry you are working in,machine learning (especially deep learning neural networks) will be on your agenda.

"From my personal experience I can tell you that companies will actively searching for you if you aquire some skills in the data science field. You do not need to know everything! Some basics can already open up a lot of doors! So diving into this topic can not only immensly improve your career opportunities but also your job satisfaction!"

It'stime to get your hands dirtyand dive into one of the hottest topics on this planet.

To me the best way to get exposure is to do it "Hands on". And that's exactly what we do. Together we will go through the whole process of data import, a little bit of data preprocessing (if necessary) , creating a neural network in keras as well as training the neural network and test it(= make predictions) / make recommendations!

The course consists of 2 parts. In the first part we will create an autoencoder neural network to learn how data compression with neural networks work. In the second part we create a neural network recommender sytem, make predictions and user recommendations.

Let's get into it. See you in the first lecture