Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

An 8-Hour Livestream Seminar Taught by Ross Jacobucci, Ph.D.

This seminar is one-part of a two-part sequence on Advanced Machine Learning methods. While this seminar focuses on applying deep learning algorithms to text and image data and insight into how deep learning methodologies can shape the design of studies, Advanced Machine Learning with R aims to provide you with the core knowledge needed to apply and evaluate advanced algorithms.

Machine learning has revolutionized the collection and analysis of complex data types such as text, images, and videos. To extract meaningful insights from these data, it has become essential to move beyond conventional statistical methods and embrace the advanced capabilities of deep learning architectures, particularly neural networks. Python is currently the dominant programming language for research and applications using deep learning due to its rich ecosystem of algorithms and robust community support.

This workshop provides hands-on experience in applying deep learning algorithms to text and image data and insight into how deep learning methodologies, such as reinforcement learning, can shape the design of studies, providing guidance on their integration into research methodologies.

We will introduce several common deep learning frameworks, including recurrent and convolutional neural networks, pre-trained large language models for sentiment analysis and text classification (e.g., BERT), and models for image classification and object detection (e.g., CLIP). Emphasis will be placed on the theoretical background of these methods and their practical applications in real-world scenarios.

The scope of applications for deep learning will be demonstrated by applying deep learning algorithms to:

• Study the language used in Reddit posts from different communities (subreddits) and develop a model that can accurately identify which subreddit a post belongs to based on its content.
• Develop a system capable of recognizing and labeling objects and text present in smartphone screenshots.
• Constructing both reinforcement learning and active learning environments that enable dynamic adjustments in study designs based on real-time feedback and insights.

By the end of the workshop, participants will have the expertise to apply these cutting-edge deep-learning techniques to their data, driving forward the frontiers of research and development in their respective fields.