Lisa is the lead data science instructor at Digital Futures, with responsibility for the design of our Data Science programme and delivery of a world-class learning experience for our engineers. Lisa has over 10 years experience in the data industry.
This 90-minute tutorial provides an introduction to using TensorFlow for building random forest models. The tutorial will begin with an overview of the random forest algorithm and its advantages in the context of machine learning. Next, participants will learn how to implement a random forest model using TensorFlow's high-level API, Keras. The tutorial will cover important concepts such as model architecture, hyperparameter tuning, and training and evaluation techniques. Additionally, participants will learn how to use TensorFlow's TensorBoard to visualize and monitor their models during training. The tutorial will conclude with a discussion of best practices and tips for improving the performance of random forest models. By the end of the tutorial, participants will have gained a solid understanding of how to use TensorFlow to build powerful and accurate random forest models.
This discussion session is for educators to talk about how we teach data science in industry and academia. It'll be a guided discussion, we'll vote on the top topics to discuss at the start and then we'll work our way through problems, solutions and new ideas. Maybe we'll get to talk about ChatGPT, or using Jupyter, or when to "teach in an IDE", or how to balance lecture vs problem solving vs homework - all topics can be up for voting at the start.
Keynote with Lisa Carpenter and Antonio Campello