Tuesday, Sept 13th (11am-12pm CT)

 

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 and take it through the steps of training and evaluating a model to make predictions using ML to predict benign and malignant tumors.

 

Tuesday, Sept 20th (11am-12pm CT)

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.

 

Tuesday, Sept 27th (11am-12pm CT) 

Introduction to Datasets

Speaker: Data Scientist, Mark III

In this session, we'll cover what datasets for Machine Learning and Deep Learning projects look like and how to find them.

This will include highlighting some of the most popular datasets in the community today as well as good sources to download these datasets from.

Some brief tips and tricks for cleaning up datasets will be covered and we'll conclude the session with a mini-workshop and lab showing how to import and interact with datasets in a Jupyter Notebook for a public health use case.

 

Tuesday, Oct 4th (11am-12pm CT) 

Accelerating Genome Sequencing Analysis with NVIDIA Clara Parabricks

Speaker: Genomics Leader, NVIDIA

In this session, we'll overview NVIDIA Clara Parabricks, a GPU-accelerated computational genomics application framework, it delivers accurate and accelerated analysis of next-generation sequencing (NGS) data for researchers, clinical teams, medical centers and sequencing centers for cancer sequencing projects, population studies, RNA-Seq, and many more applications.

 

Tuesday, Oct 11th (11am-12pm CT) 

Introduction to Computer Vision

Speaker: Data Scientist, Mark III 

In this session, we'll cover the basics around what computer vision is, how it works (classification, object detection, segmentation), some of the popular frameworks and models used today, and what some of the practical applications might be in research and industry.  We'll also walk through what a typical Computer Vision project lifecycle might look like.

We'll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we'll use code examples to build a CNN image classifier as well as using pretrained model libraries for object detection and image segmentation.