Vijay Reddy walks you through the process of building machine learning models with TensorFlow. You'll learn about data exploration, feature engineering, model creation, training, evaluation, deployment, and more.
Enterprise and organizational adoption, Extensions and customization, Usage and application
Hands-on data science with Python
Zachary Glassman (The Data Incubator)
Zachary Glassman leads a hands-on dive into building intelligent business applications using machine learning, walking you through all the steps of developing a machine learning pipeline. You'll explore data cleaning, feature engineering, model building and evaluation, and deployment and extend these models into two applications using real-world datasets.
Explore the AWS machine learning platform using Amazon SageMaker
Wenming Ye (Amazon Web Services), Miro Enev (NVIDIA)
Wenming Ye and Miro Enev offer an overview of deep learning along with hands-on Jupyter labs, demos, and instruction. You'll learn how DL is applied in modern business practice and how to leverage building blocks from the Amazon ML family of AI services.
Reproducible research best practices (highlighting Kaggle Kernels)
Rachael Tatman (Kaggle)
Rachael Tatman shows you how to take an existing research project and make it fully reproducible using Kaggle Kernels. You'll learn best practices for and get hands-on experience with each of the three components necessary for completely reproducible research.
JupyterCon Networking Happy Hour
Kick off a great week at JupyterCon by meeting some of your fellow attendees at a casual happy hour.