AI Camp
An Exploration of AI, Deep Learning & Machine Learning
Sun. Nov. 19 from 09:00 am to 06:00 pm
AI Camp is a grassroots, community-run open-source conference focused on open source AI technologies, including AI, machine learning and deep learning.
Our content is geared towards developers seeking to learn more about enterprise open source best practices, insights and emerging technologies.
Tickets
Sponsors
If you or an organization you know may be interested in sponsorsing AI Camp please see out prospectus Prospectus and reach out to us by email.
Presenters
AI camp features a rich mix of presenters from across the open source community.
Schedule
We will be adding schedule details in the next few days which specify the detailed order/timing of presentation on Sun. Nov. 19, between 9am - 6pm.
Presentations
AI Camp includes an interesting mix of presentation on best practices, emerging techniques, recent research and case studies regarding open source AI technologies.
Open-Source AI Tools (Python and R)
Are you wanting to get started with data science, but don't know where to begin? This talk with give an in-depth assessment of the strengths and weaknesses of open-source Python and R tools for data science, machine learning, and artificial intelligence.
Scheduled For
Build Intelligent Applications with Azure Cognitive Service and CNTK
Microsoft Cognitive Services enables developers with powerful set of APIs that can be used to develop intelligent apps with powerful algorithms, using just a few lines of code.The API enables developers to easily add intelligent features – such as emotion and video detection; facial, speech and vision recognition; and speech and language understanding – into their applications with minimum effort. This session will show case how to get started with the API and how it can be integrated with your application. The session will also discuss the CNTK that runs behind the screen.
Eliminating Hiring Bias With AI
Bias, both conscious and unconscious, negatively affects hiring for both candidates and companies alike. By leveraging AI to ascertain candidate suitability, regardless of their identity (gender, race, nationality etc.), we can make hiring more fair for everyone, and build stronger workforces. This presentation will show how bias-free candidate screening using AI works.
Getting Started with Machine Learning on Apache Spark
Join us for a basic introduction to Apache Spark with Jerome Nilmeier, Data Scientist and Apache Spark expert, to learn how to get started with Machine Learning using Scala and Apache Spark. After this training you will be able to write and run a sample Scala application using Apache Spark.
Attendees will learn: Fundamentals of Scala. Why Scala is best for leveraging Apache Spark (we will also review other languages: Python, R)Fundamentals of Apache SparkCoding examples from all of the main libraries of Apache Spark (SparkSQL, MLlib, GraphX, Spark Streaming, and SparkR), with particular emphasis on the machine learning libraries, including open source projects that run on the Spark framework (SystemML, R4ML).
TensorFlow's support for Deep Learning
Developers building model for Deep Learning now have some 15 major/minor frameworks to choose from. Such a wide set of choices reflects the level of interest in Deep Learning across academia and enterprises, but choosing an appropriate framework can be confusing given the trade-off among them.
In this talk, we will take a close look at the capabilities of TensorFlow, the open source framework from Google that currently has the highest rate of adoption. We will cover the extensive language API's, high level API's, scaling the training across CPU and GPU with distributed mode, and the recently announced eager execution mode. We will also demonstrate the tools for debugging, visualization and model serving.
Cervical Cancer Detection using Conv Nets
AI Diagnostics would help millions of women, particularly in developing nations without pathologists. We explore the challenges involved in creating an optimal AI Diagnostic tool using convolutional neural networks to solve this problem. What exactly goes into priming the hyperparameters? How do we augment the data and what is the best way to continue training our AI so that it continues rising in accuracy?
Scheduled For
Data Cleaning vs. Human Curation
Integrating big data usually requires cleaning, in order to fit the constraints of the integrated system. But if data is organized as a graph rather than as a tree, we can gain the flexibility we need. Cleaning becomes an option rather than a prerequisite. I will present real world examples of this approach, exposing some of its benefits.
Intro to Medical Imaging with TensorFlow
A discussion of recent applications of Deep Learning to medical imagining, including Pathology and Skin Cancer detection. I'll also introduce open source image classification packages in TensorFlow you can use for your own projects.
News
We'll be posting any News or update here, so please stay tuned for any important announcements.
Location
Our venue is Convene's midtown NYC location at 730 3rd Ave, where we'll be hosting along with other Open Camps events. We'll be posting further venue details here as the event approaches, including access and check-in procedures.
Team
AI Camp is organized by a volunteer team from the open source community. If you'd like to get involved, please reach out to us by email .
