YoVDO

Adversarial Validation and Training in Stock Market Price Prediction

Offered By: Open Data Science via YouTube

Tags

Machine Learning Courses Recommender Systems Courses Financial Markets Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Dive into a 28-minute conference talk exploring Adversarial Validation and Training techniques for Stock Market Price Prediction. Learn about concept drift, stock market forecasting, and dataset analysis. Understand the ideal transaction process and delve into adversarial training and validation methods. Explore the world of recommender systems, their impact on various industries, and the challenges faced by traditional algorithms. Discover the rising importance of graph-based models like PinSage, GraphSage, and GNNs in addressing these challenges. Gain valuable insights from experts Giacomo Maccagni and Federico Minutoli of Machine Learning Reply on applying advanced machine learning techniques to financial markets.

Syllabus

Unlock the secrets of Adversarial Validation and Training in Stock Market Price Prediction with Giacomo Maccagni and Federico Minutoli of Machine Learning Reply! In this talk, you’ll dive into the dynamic world of recommender systems, where we unravel the impact on information overload, user satisfaction, and revenue growth in industries like e-commerce and streaming services. Discover the challenges of traditional algorithms and the recent surge in graph-based models such as PinSage, GraphSage, GNNs, and more.
- Introductions
- Concept Drift
- Stock Market Forecasting
- Stock Market Dataset
- Ideal Transaction
- Adversarial Training
- Adversarial Validation


Taught by

Open Data Science

Related Courses

Introduction to Recommender Systems
University of Minnesota via Coursera
Text Retrieval and Search Engines
University of Illinois at Urbana-Champaign via Coursera
Machine Learning: Recommender Systems & Dimensionality Reduction
University of Washington via Coursera
Java Programming: Build a Recommendation System
Duke University via Coursera
Introduction to Recommender Systems: Non-Personalized and Content-Based
University of Minnesota via Coursera