The Sheikh Zayed Institute for Pediatric Surgical Innovation, NVIDIA and Mark III Systems would like to host an AI/Machine Learning Education Series for Children's National Hospital and its greater community in 2023. This bi-weekly education series is 100% virtual and will include both tutorials and virtual "rapid labs" for attendees delivered via Jupyter Notebook. There will be a series of sessions that will feature industry experts in Machine Learning, who will dive into current trends around AI/ML. We hope you can join us!
AI/ML Education Series (Intro Track):
Replays (Past Sessions):
Thursday, Sept 7th (2pm-3pm ET)
Intro to Jupyter Notebooks, Basic Data Operations, Pandas, and DataFrames
Speaker: Data Scientist, Mark III
In this session, we'll cover a series of fundamentals needed for Machine Learning and Deep Learning projects, focused around tooling and dataset strategies.
This session will include an introduction to Jupyter Notebooks and a tour of basic data operations, including the usage of Pandas and DataFrames.
This module will also include a Jupyter Notebook lab that will focus on basic data operations around two sets of cardiology data and prepping the dataset for ML and DL training.
Thursday, Sept 21st (2pm-3pm ET)
Introduction to Machine Learning and AI: What is it and why we do we need it?
Speaker: Data Scientist, Mark III
In this session, we’ll cover the basics around what Machine Learning is, look at the different ML techniques and methods, examine what a typical ML project lifecycle looks like, and discuss some of the most commonly used example algorithms.
This session will also include a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use an example dataset from Kaggle and take it through the steps of training and evaluating a model to make predictions using ML. Specifically the use case will cover using quantitative data to perform anamoly detection based on a quantitative dataset from a complex system.
Thursday, Oct 5th (2pm-3pm ET)
Applying Machine Learning to Tabular Data (EHR Data)
Speaker: Data Scientist, Mark III
In Part 2 of this 2-part session on Machine Learning, we’ll cover techniques on how to apply ML to make predictions, specifically on tabular data.
This session will include a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use an example EHR dataset and take it through the steps of training and evaluating a model to make predictions using ML. Specifically the use case will cover using quantitative data to predict benign and malignant tumors, based on a large dataset.
Thursday, Oct 19th (2pm-3pm ET)
Intro to Deep Learning: An Introduction to Neural Networks
Speaker: Data Scientist, Mark III
In this session, we'll cover the basics around what Deep Learning is, look at how it fits within the AI/ML universe, dive into neural networks (including CNNs, LSTMs, and GANs), and walk through a typical Deep Learning project lifecycle.
We'll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use an example dataset (CIFAR-10) to train and evaluate a neural network model using Keras.