Nick Locascio

Deep Learning Researcher, Author, Consultant, Entrepreneur.


6.S191: Intro to Deep Learning

Founded and taught MIT’s first course on Deep Learning and TensorFlow with sponsorship from Google Brain, NVIDIA, Amazon Echo, and IBM Watson. Website here. Lecture videos here.

Machine Learning with Scikit-Learn and Tensorflow

Created online video course about Machine and Deep Learning with Packt Publishing. Features full coverage of machine learning concepts from core fundamentals to working implementation. Early release is out now (here), final release out Q2 2018.


Fundamentals of Deep Learning (O’Reilly Book)

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field.

Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.

High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision

Journal of Radiology 2017. Paper here. MIT News.

Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge

First Author, EMNLP 2016. Designed and trained novel Deep RNN for generating Regular Expressions given natural language descriptions of the user’s intent. Paper here. Code+Data here.

Industry Experience


Deep Learning Consultant. Built deep learning systems for dynamic cyber threat and insurance modeling. Also worked on cybersecurity machine learning theory as it relates to the bounds on cyberinsurance market profitability.

Perch Fitness

Computer Vision Engineer. Developed automatic exercise classification from video with deep CNN’s. Developed facial recognition login, barbell path tracking, and form tracking systems.


Machine Learning Engineer. Worked on Recommendations team building machine learning models with big data pipelines. Ran user-facing experiments on Re-Ranking Homefeed using Facebook data signals. Built internal debug tool for our machine learning ranking models.


Software Engineer. Worked on iOS team. Leveraged runtime meta programming to implement property-based wrapper for NSUserDefaults. Worked on experimental Notifications Center Widget.

My Projects


Chrome Extension that performs image captioning using deep neural networks to automatically provide alt-text for vision-impaired users.


Web app and deep learning system that listens to company meetings to monitor employee speaking habits and tendencies. Speaker + interruption recognition in a novel setting.

Mystery Snap

iOS photo sharing application. +250,000 users. +3 million photos sent.

Lecture Dashboard

Node + Socket web app that gives professors real-time feedback during lecture. Also built an Internet of Things Arduino controlled LED Orb that changed color in real time to match the on-screen graph. Code here.

Monster Cats

iOS 2D action runner game. +150,000 downloads.

Various Other Projects

Portfolio of other design and software projects.

Other Writings

My Blog