$167 – $497

Future Labs AI Summit - Training + Conference - New York

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Kimmel Center for University Life

60 Washington Square South

New York, NY 10012

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Description

NYU students interested in attending the training sessions receive a training discount. Please email Mina Salib at mina@nyu.edu for the code.


DAY 1 | MONDAY, OCT. 30 – Includes all sessions.

Session 1: Intro to Machine Learning with Ross Fadely of Insight Data Science

You will be introduced to some of the core concepts needed to jump into Machine Learning (ML). In addition, we will briefly discuss how teams across many different industries and verticals are using ML in practice. We will dive into some ML case studies using Python and Scikit-Learn. Finally, we will wrap up with some best practices and guidance for continued learning about ML.

You'll leave with,

  • An understanding of how to analyze data using machine learning algorithms.
  • How algorithms should be structured to make the most use of the data you have available

Prerequisites: A working knowledge of Python

Installation requirements: To live run exercises requires a laptop with Python, Numpy, Scipy, and Scikit-Learn installed.


Session 2: Machine Learning for Statisticians with George Lentzas, Ph.D. in Machine Learning from Oxford Currently a Professor of Machine Learning at Columbia University and co-founder of Springfield Capital

Performance of machine learning models critically depends on their ability to make accurate predictions in out of sample, a.k.a. “test” datasets. Here we will discuss how to evaluate the performance of different machine learning models and how to select the “best” machine learning model.

You'll leave with,

  • You will come away with understanding the difference between machine learning models.
  • How to identify the best model to solve different problem sets

Prerequisites: A working knowledge of Python and a background in statistics

Installation requirements: To live run exercises requires a laptop with Python, Numpy, Scipy, and Scikit-Learn installed.


Session 3: Intro to Deep Learning - Instructor, TBD

As you delve deep into the field of artificial intelligence you will come across the phrase "deep learning" quite often. To hone your skills in the field, it's important to understand what deep learning is, how it differs from machine learning, and the relation between supervised learning, back propagation, stochastic gradient descent, activation functions, and the basic linear unit.

You'll leave with,

  • An understanding of distinctions between traditional machine learning and deep learning
  • Learn some deep learning examples, like Convolutional Neural Networks (CNN) for Image Recognition
  • How to apply it to real life problem sets

Prerequisites: A working knowledge of Python and an understanding of machine learning concepts.

Installation requirements: To live run exercises requires a laptop with Python, Numpy, Scipy, and Scikit-Learn installed.


Session 4: Understanding and Implementing Deep Learning techniques: Linear Regression and Gradient Descent. Instructor TBD

  • The difference between gradient descent and stochastic gradient descent
  • How to use stochastic gradient descent to learn a simple linear regression model
  • How to put together a simple gradient descent using a cost function

Prerequisites: A working knowledge of Python and an understanding of machine learning concepts.

Installation requirements: To live run exercises requires a laptop with Python, Numpy, Scipy, and Scikit-Learn installed.


Session 5: To Be Announced


7:00pm - 9:00PM: Future Labs AI Summit Kick Off Happy Hour



DAY 2 | TUESDAY, OCT. 31

11:00am - 5:00pm

Included in your ticket purchase is Day 2 of the Future Labs AI Summit, a full day of presentations and panels with talks from leaders in AI as well as demos from the second cohort of the AI NexusLab. See full details here.

Confirmed Speakers:

  • Corinna Cortes, Head of Google Research, NY
  • Richard Zemel, Co-Founder, and Director of Research, Vector Institute for Artificial Intelligence
  • Tess Posner, Executive Director at AI 4 ALL
  • Anand Sanwal, CEO, CB Insights
  • Dennis Mortensen, CEO, x.ai
  • Josh Sutton, Global Head, Data & Artificial Intelligence, Publicis.Sapient
  • Evan Nisselson, General Partner, LDV Capital
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Date and Time

Location

Kimmel Center for University Life

60 Washington Square South

New York, NY 10012

View Map

Refund Policy

Refunds up to 7 days before event

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