05-19, 11:00–11:55 (Europe/Vilnius), Coral A - Workshop
Are you curious about how recommendation engines work? In this workshop, we'll dive deep into the world of TensorFlow Recommender Systems, exploring the fundamental concepts, techniques, and tools needed to build effective recommendation engines. We'll start with an overview of the different types of recommender systems, including collaborative filtering, content-based filtering, and hybrid models. We'll also explore evaluation metrics and learn how to measure the effectiveness of these models.
The workshop then shifts to hands-on exercises that allow you to build your own recommendation engine using TensorFlow. You'll learn how to prepare data, train the model, and make recommendations. Through guided examples, you'll gain a practical understanding of the end-to-end process of building a recommendation engine.
In today's digital world, personalized recommendations have become an essential part of user engagement and retention. With the abundance of data available, building effective recommendation systems can seem daunting. In this workshop, we will take a deep dive into the world of TensorFlow Recommender Systems and explore the techniques and tools necessary to build a high-performing recommendation engine.
We will start by understanding the fundamentals of recommender systems and how TensorFlow can be used to build them. We will then explore the different types of recommenders, including content-based, collaborative filtering, and hybrid models. We will also delve into the various evaluation metrics used to measure the effectiveness of recommender systems.
In the second half of the workshop, we will get hands-on experience with TensorFlow Recommender Systems. We will work through a real-world use case and learn how to prepare the data, build and train the model, and make recommendations.
By the end of the workshop, attendees will have a solid understanding of the key concepts and tools required to build powerful recommender systems using TensorFlow. They will have the opportunity to apply what they have learned and create their own personalized recommendations. Whether you're a data scientist, engineer, or product manager, this workshop is the perfect opportunity to dive deeper into the world of TensorFlow Recommender Systems and take your skills to the next level.
Intermediate
What topics define your talk the best? –python, open source, PyData, data science, machine learning
Ashmi is a doctoral researcher at the Technical University of Munich, where her research focuses on Recommender Systems and Human-Computer Interaction. She graduated with a master's degree in Computer Science in 2019 from the same university.
She is passionate about using technology to automate tedious tasks and is always excited to tackle new technical challenges. Recently, she was honored with the DevelopHER Awards 2022 in the Emerging Talent category by DevelopHER UK. Since 2023, she also holds the title of Google Developer Expert (GDE) in Machine Learning.
As a Google Women Techmakers (WTM) Ambassador diversity advocate, she is dedicated to closing the gender gap in STEM through her involvement in various women in STEM networks.
When not sitting in front of her computer, she is either traveling or training to become a triathlete. 🏊♀️ 🚴 🏃♀️