Recommender Systems and Deep Learning in Python

The most in-depth course on recommendation systems with deep learning, machine learning, data science, and AI techniques

Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer

Created by: Lazy Programmer Team
Artificial Intelligence and Machine Learning Engineer

What Will I Learn?

• Understand and implement accurate recommendations for your users using simple and state-of-the-art algorithms
• Big data matrix factorization on Spark with an AWS EC2 cluster
• Matrix factorization / SVD in pure Numpy
• Matrix factorization in Keras
• Deep neural networks, residual networks, and autoencoder in Keras
• Restricted Boltzmann Machine in Tensorflow

Requirements

• For earlier sections, just know some basic arithmetic
• For advanced sections, know calculus, linear algebra, and probability for a deeper understanding
• Be proficient in Python and the Numpy stack (see my free course)
• For the deep learning section, know the basics of using Keras

Target audience

• Anyone who owns or operates an Internet business
• Students in machine learning, deep learning, artificial intelligence, and data science
• Professionals in machine learning, deep learning, artificial intelligence, and data science