Schedule:

6:00-7:00pm Networking and light food

7:00-7:10pm Announcements

7:10-8:00pm Math Primer - Jen Hsin

8:00-9:00pm Introduction to TensorFlow and Machine Learning - David Clark

Abstract/Speaker Bios:

Math Primer - Jen Hsin

Jen will present a Math Primer focused on structure in data and making predictions with models.

Jen Hsin is a senior data scientist at Google.  Before joining Google, she was a postdoc at Stanford doing research in physics/biophysics/computational biology/bacterial genetics.

Introduction to TensorFlow and Machine Learning - David Clark

David will present an introduction to TensorFlow using the Wine dataset from the UC Irvine Machine Learning Repository. The talk begins with a data preparation section employing routines from the Python libraries Pandas and Seaborn. Then, I model the data using logistic regression in Skflow. I finish the talk with TensorFlow, where I use a softmax regression model and cross entropy to minimize the gradient descent. The last section includes a demonstration of Tensorboard which is a great tool to visualize the modeling done by TensorFlow.

David Clark has a background in astrophysics, where he used Python extensively to analyze astronomical images and spectra. He has recently transitioned careers to data science. Currently he is doing work for the startup Palo Alto Scientific, Inc., using the machine learning library TensorFlow. He is also doing work for the startup Quantea, making a dashboard using the Python libraries Bokeh and Pandas.