Dive into the second part of a comprehensive conference talk from KDD 2020 exploring the practical applications of deep learning in search and recommender systems. Learn from LinkedIn Corporation experts as they delve into crucial aspects such as environment setup, preprocessing techniques, text preprocessing methods, data preparation strategies, model training approaches, and result analysis. Gain valuable insights into how these advanced technologies are implemented in real-world scenarios to enhance user experiences and improve recommendation accuracy.
Deep Learning for Search and Recommender Systems in Practice - Part 2
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Introduction
Environment Setup
Preprocessing
Text Preprocessing
Data Preparation
Model Training
Results
Taught by
Association for Computing Machinery (ACM)
Related Courses
-
Deep Learning for Search and Recommender Systems in Practice - Part 1
-
Recommender Systems and Deep Learning in Python
-
Train compute-intensive models with Azure Machine Learning
-
Text Retrieval and Search Engines
3.2 -
Deep Learning for Search and Recommender Systems in Practice
-
Production Machine Learning Systems
