### Upcoming in 2018

- July 21st to August 18th -- Deep Learning,
*NYC Data Science Academy* - October 20th to December 1st -- Deep Learning,
*NYC Data Science Academy*

### 2018

- 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)