Published 11/2022Created by AI Sciences,AI Sciences TeamMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 99 Lectures (8h 11m ) | Size: 3.34 GB
What you'll learn Learn the about basics of recommender systems
Learn the basics impact of recommender systems with integrated artificial intelligence
Learn about the major challenges and applications of recommender systems
Learn the basic taxonomy of recommender systems
Learn the impact of overfitting, underfitting, bias and variance
Learn the fundamental concepts of content based filtering and collaborative filtering
Learn the hands-on development of recommender system using machine learning topologies with python
Learn building the recommender system for various recommender system applications such as Spotify song recommending systems using machine learning and python
Hands on experience to build content-based recommender systems with machine learning and python
Hands on experience to build item-based recommender systems using machine learning techniques and python
Learn to model k-nearest neighbors-based recommender ee for various types of applications of recommender systems in python
Learn the about deep learning of recommender systems
Learn the about benefits and challenges of deep learning in recommender systems
Learn about the mechanism of generic deep learning-based approaches for recommender system
Learn the basic neural network models for recommendations
Learn the theoretical aspects of neural collaborative filtering and variational auto encoders for collaborative filtering
Learn the hands-on practice for the implementation of deep learning-based recommender system
Learn about the implementation of two-tower model and its implementation for development of recommender systems
Learn the implementation of TensorFlow recommenders for the development of recommender systems
And much more.
Requirements No prior knowledge of Recommender Systems, Machine Learning, Data Analysis or Mathematics is needed.