Kulkarni, Akshay
Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, Nlp and Graph-Based Techniques
- ISBN 13:
- 9781484289532
- author:
- Kulkarni, Akshay
- format:
- Paperback
- publisher:
- APress
- language:
- English
- Publication Year:
- 2022
- Pages:
- 632
- Dimensions:
- 25.4 x 17.8 x 1.4 centimetres (0
- Genre:
- Computers, Programming, Python,
- Condition:
- New
- Availability:
- Item usually sent within 2 working days
Description
Build Recommender Systems with Python This book teaches you how to build recommender systems using machine learning algorithms in Python. You'll start by learning about basic concepts and different types of recommender engines, before moving on to traditional algorithms such as market basket analysis and content-based systems that incorporate natural language processing. You'll then explore techniques like collaborative filtering using matrix factorization and hybrid systems that combine both content-based and collaborative filtering methods. The book also covers machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest, as well as NLP, deep learning, and graph-based techniques to build a recommender engine. By the end of this book, you'll understand how to build recommender systems with various tools and techniques using machine learning, deep learning, and graph-based algorithms.
Related Products
Related Products
Building Recommendation Systems in Python and Jax: Hands-On Production Systems at Scale
Bischof, Bryan
Applied Deep Learning with Python
Galea, Alex
Machine Learning: Make Your Own Recommender System (Machine Learning from Scratch)
Theobald, Oliver
Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
Labonne, Maxime
Systems Engineering Demystified - Second Edition: Apply modern, model-based systems engineering techniques to build complex systems
Holt, Jon