### 2019

April 13th PM — Unit 10: Deep Reinforcement Learning,

*NYC Data Science Academy*[slides] [video presentation of final project from student, Zach Do]April 13th AM — Unit 9: Generative Adversarial Networks,

*NYC Data Science Academy*[slides]April 6th — Units 7 and 8: Deep Learning with TensorFlow,

*NYC Data Science Academy*[slides]March 30th — Units 5 and 6: Natural Language Processing,

*NYC Data Science Academy*[slides]March 23rd PM — Unit 4: Machine Vision,

*NYC Data Science Academy*[slides]March 23rd AM — Unit 3: Building and Training a Deep Learning Network,

*NYC Data Science Academy*[slides]March 16th PM — Unit 2: How Deep Learning Works,

*NYC Data Science Academy*[slides]March 16th AM — Unit 1: The Unreasonable Effectiveness of Deep Learning,

*NYC Data Science Academy*[video interview] [code] [slides]March 6th — Deep Learning Illustrated: A Course Demo,

*NYC Data Science Academy*[slides] [slides of former student, Zach McCormick]

### 2018

December 1st PM -- Unit 10: Deep Reinforcement Learning,

*NYC Data Science Academy*[slides]December 1st AM -- Unit 9: Generative Adversarial Networks,

*NYC Data Science Academy*[slides]November 27th — Artificial Intelligence Panel,

*VIOCON, Nasdaq Marketplace, New York*November 17th -- Units 7 and 8: Deep Learning with TensorFlow,

*NYC Data Science Academy*[slides]November 3rd -- Units 5 and 6: Natural Language Processing,

*NYC Data Science Academy*[slides]October 27th PM -- Unit 4: Machine Vision,

*NYC Data Science Academy*[slides]October 27th AM -- Unit 3: Building and Training a Deep Learning Network,

*NYC Data Science Academy*[slides]October 26th — E6885 (Reinforcement Learning) Guest Lecture, Columbia University [slides]

October 20th PM -- Unit 2: How Deep Learning Works,

*NYC Data Science Academy*[slides]October 20th AM -- Unit 1: The Unreasonable Effectiveness of Deep Learning,

*NYC Data Science Academy*[video interview] [code] [slides]October 10th — The Origins of Deep Learning’s Unreasonable Effectiveness,

*NYC Open Data*[slides]September 12th -- Deep Machine Learning and its Neuroscience Origins,

*Pintô, New York*August 18th PM -- Unit 10: Deep Reinforcement Learning,

*NYC Data Science Academy*[slides]August 18th AM -- Unit 9: Generative Adversarial Networks,

*NYC Data Science Academy*[slides]August 11th -- Units 7 and 8: Deep Learning with TensorFlow,

*NYC Data Science Academy*[slides]August 7th -- Talent Intelligence: A Think Tank on AI in HR by untapt,

*Rise New York*[slides] [press release]August 4th -- Units 5 and 6: Natural Language Processing,

*NYC Data Science Academy*[slides]July 28th PM -- Unit 4: Machine Vision,

*NYC Data Science Academy*[slides]July 28th AM -- Unit 3: Building and Training a Deep Learning Network,

*NYC Data Science Academy*[slides]July 21st PM -- Unit 2: How Deep Learning Works,

*NYC Data Science Academy*[slides]July 21st AM -- Unit 1: The Unreasonable Effectiveness of Deep Learning,

*NYC Data Science Academy*[blog post] [video interview] [code] [slides]July 9th -- Deep Learning with Artificial Neural Networks,

*Columbia University College of Dental Medicine*[slides]May 30th -- untapt Resume Clinic,

*NYC Data Science Academy*[slides]April 7th PM -- Unit 10: Deep Reinforcement Learning,

*NYC Data Science Academy*[slides]April 7th AM -- Unit 9: Generative Adversarial Networks,

*NYC Data Science Academy*[slides]March 24th -- Units 7 and 8: Deep Learning with TensorFlow,

*NYC Data Science Academy*[slides]March 17th -- Units 5 and 6: Natural Language Processing,

*NYC Data Science Academy*[slides]March 10th PM -- Unit 4: Machine Vision,

*NYC Data Science Academy*[slides]March 10th AM -- Unit 3: Building and Training a Deep Learning Network,

*NYC Data Science Academy*[slides]March 3rd PM -- Unit 2: How Deep Learning Works,

*NYC Data Science Academy*[slides]March 3rd AM -- Unit 1: The Unreasonable Effectiveness of Deep Learning,

*NYC Data Science Academy*[blog post] [video interview] [code] [slides]February 20th -- Deep Learning Course Demo,

*NYC Open Data*[slides]February 17th --

*hosted*Deep Reinforcement Learning II,*untapt*(NY) [notes] [blog post]January 19th to 21st -- filming Deep Reinforcement Learning and Generative Adversarial Network LiveLessons for

*Safari*[code] [blog post] [summary post]

### 2017

December 16th PM -- Unit 10: Deep Reinforcement Learning,

*NYC Data Science Academy*[slides]December 16th AM -- Unit 9: Generative Adversarial Networks,

*NYC Data Science Academy*[slides]December 9th --

*hosted*Deep Reinforcement Learning,*untapt*(NY) [notes] [blog post]December 2nd -- Units 7 and 8: Deep Learning with TensorFlow,

*NYC Data Science Academy*[slides]November 21st -- Fundamentals of Deep Learning,

*untapt*(NY) [slides]November 18th -- Units 5 and 6: Natural Language Processing,

*NYC Data Science Academy*[slides]November 3rd -- E6885 (Reinforcement Learning) Guest Lecture,

*Columbia University*(NY) [slides]October 28th PM -- Unit 4: Machine Vision,

*NYC Data Science Academy*[slides]October 28th AM -- Unit 3: Building and Training a Deep Learning Network,

*NYC Data Science Academy*[slides]October 17th -- Reinforcement Learning,

*untapt*(NY) [blog post]October 14th PM -- Unit 2: How Deep Learning Works,

*NYC Data Science Academy*[slides]October 14th AM -- Unit 1: The Unreasonable Effectiveness of Deep Learning,

*NYC Data Science Academy*[blog post] [video interview] [code] [slides]September 27th -- Deep Learning Course Demo,

*NYC Open Data*[slides]September 15th to 18th -- filming Deep Learning for Natural Language Processing LiveLessons for

*Safari*[code] [blog post]August 5th -- Model Architectures for Answering Questions and Overcoming NLP Limits,

*untapt*(NY) [notes]July 1st -- Models with Attention,

*untapt*(NY) [blog post] [notes]June 8th -- Match Making for Tech Jobs,

*International Society for Business and Industrial Statistics*(IBM TJ Watson Research Center, Yorktown Heights, NY)June 1st to 3rd -- filming Deep Learning with TensorFlow LiveLessons

*Safari*[code] [blog post] [free preview]May 5th -- Panel Discussion on "Becoming a Champion" of Diversity,

*HackFemme Conference*(NY)May 1st --

*Metis Data Science Bootcamp*(NY) [slides]April 21st -- NYU Analytics Conference,

*New York University*(NY)April 19th -- Recurrent Neural Networks, including Gate Recurrent Units and Long Short-Term Memory units,

*untapt*(NY) [blog post] [notes]March 27th -- Building Deep Learning Models for Natural Language Processing,

*untapt*(NY) [blog post] [notes]March 6th -- Word Vectors and Vector-Space Embeddings,

*untapt*(NY) [blog post] [notes]February 28th -- Fundamentals of Deep Learning, with Applications,

*NYC Open Data*(NY) [video] [slides]February 7th -- Unsupervised Learning,

*untapt*(NY) [blog post] [notes]January 30th -- The Fundamentals of Deep Learning, with Applications,

*Open Statistical Progamming Meetup*(NY) [slides] [summary]January 17th --

*Metis Data Science Bootcamp*(NY) [slides]January 12th -- Implementing Convolutional Nets,

*untapt*(NY)January 4th -- Deep Learning with Artificial Neural Networks,

*Wilfrid Laurier University*(Waterloo) [press release] [video] [slides] [summary]

### 2016

A History of Biological and Machine Vision,

*untapt*(NY)How Deep Convolutional Neural Networks Work and How to Improve Them,

*untapt*(NY)Fundamentals of Deep Learning with Neural Networks,

*Data Science + FinTech*(Jersey City, NJ)Proofs of Key Deep Neural Network Properties,

*untapt*(NY)Improving Deep Neural Networks,

*untapt*(NY)The Backpropagation Algorithm,

*untapt*(NY)Perceptrons and Sigmoid Neurons,

*untapt*(NY)Predicting Job Application Success with Two-Stage, Bayesian Modeling of Features Extracted from Candidate-Role Pairs.

*Joint Statistical Meetings*(Chicago)Modeling the Success of Software Developer Job Applications.

*Women in Machine Learning and Data Science*(NY)Modeling the Success of Software Developer Job Applications.

*Metis Data Science Bootcamp, Winter Cohort*(NY)R and Python Bootcamp.

*Columbia University / Hunter College PhD Career Transitions*(NY)Mock Interviews for Data Scientists.

*Metis Data Science Bootcamp, Spring Cohort*(NY)Mock Interviews for Technology Careers.

*General Assembly*(NY)

### 2015

Winner of Data Science Hackathon at

*I-COM Global Summit*(San Sebastián, Spain)Winner of Data Science Hackathon at

*Google-Omnicom Emerge*(NY)Data Science: Applications, Trends and Technologies.

*Metis Data Science Bootcamp, Fall Cohort*(NY)Data Science Career Panel.

*Columbia University / Hunter College PhD Career Transitions*(NY)Data-Driven Healthcare Marketing.

*Omnicom Emerge+ Healthcare*(London)

### 2014

Data Science in the Online Advertising Ecosystem.

*New York Computer Science and Economics Day*[blog post]Data Science at Omnicom.

*General Assembly*(NY)

### 2013

Genes Contributing to Variation in Fear-Related Behaviour.

*Wellcome Trust Centre for Human Genetics*(Oxford) [dissertation] [review]

### 2011

Fine-Mapping QTL and Inferring Causal Pathways that Underlie Sixty Murine Phenotypes.

*Mouse Genetics*(Washington, DC)Early-onset mood and anxiety problems: the role of early life adversities, epigenetic mechanisms and continuing brain development [Seminar Chair].

*Genetics of Mood*(Oxford)Pharmatics: Machine Learning for Identifying Causal Relationships with Genomic Data.

*Kairos Global Summit*(NY)Pharmatics: Machine Learning for Identifying Causal Relationships with Genomic Data.

*Venture Capital Investment Competition, European Final*(Oxford)

### 2010

Gene-by-Environment Interactions Underlying Anxiety Across Six Murine Experiments.

*Complex Trait Community Annual Meeting*(Chicago)Sex-by-Gene Interactions in 100 Murine Phenotypes Investigated by Resample Model Averaging.

*European Mathematical Genetics Meeting*(Oxford)