Boston | April 13th – April 17th, 2020

ML for Programmers

Learn the essentials to become a skilled Artificial Intelligence Engineer
Register now

With the rapid growth of Artificial Intelligence comes rising demand for AI engineers and programmers. Ubiquitous AI-driven software that utilizes deep learning and machine learning models to enable conversational AI, autonomous machines, machine vision, and other AI technologies require serious engineering. These projects of the future promise to be some of the most exciting jobs in software engineering today.

An ML engineer works at the intersection of software engineering and data science. At ODSC, build on your programming skills to engineer the next generation of artificial intelligence-enabled software. You will learn from leading experts everything from data wrangling, modeling, and workflow to essential deep learning and machine learning frameworks.

Some of Current ML for Programmers Speakers

AI and Cloud Architect & AuthorNew Relic, Inc | Wiley

Dan Sullivan, PhD

Dan Sullivan is a Principal Engineer and Architect with New Relic where he focuses on cloud architecture, data science, machine learning, and data architecture. He is the author of six books, most recently on cloud and NoSQL databases, as well as several online courses on machine learning, data science, and cloud computing that have had over 1 million views. Dan holds a doctorate in genetics, bioinformatics, and computational biology. His peer-reviewed research has been published in PloS One, Nucleic Acid Research, Infection and Immunity, and the Journal of Proteomics and Genomics Research.

Lead Data Storytelling TrainerStoryIQ

Diedre Downing

Diedre is a Lead Data Storytelling Trainer at StoryIQ where she helps organizations improve their communication with and about data. An accidental math teacher, Diedre learned the power of demystifying numbers in New York City classrooms and the power of influencing decision-makers with data during her time running WeTeachNYC.org for the NYC Department of Education. Diedre is an Adjunct Lecturer at Hunter College in New York and has spoken at NCTM, iNACOL, and Learning Forward about adult learning methodology and best practices in professional learning.

The Art (and Importance) of Data Storytelling(Talk)

Sr. Principal Marketing ManagerRed Hat

Abhinav Joshi

Abhinav Joshi is a Sr. Principal Marketing Manager at Red Hat, focused on AI/ML workloads on Kubernetes and Containers powered Red Hat OpenShift Hybrid Cloud Platform. Abhinav has over 19 years of broad industry experience around Hybrid Cloud, Big Data Analytics, Data Management, and Digital Workspace focused products and solutions. Throughout his career, Abhinav has held strategic roles in Product Management, Marketing, Sales, and Consulting Services. He holds MS in Systems Engineering from the University of Maryland College Park, Graduate Certificate in Strategic Management from Harvard University, and a BS in Chemical Engineering from Nagpur University, India.

Accelerate ML Lifecycle with Kubernetes and Containerized Data Science Tools (Talk)

Author, Research Scientist, Core Contributor of scikit-learnColumbia Data Science Institute

Andreas Mueller, PhD

Andreas Mueller is an Associate Research Scientist at the Data Science Institute at Columbia University and author of the O’Reilly book “”Introduction to machine learning with Python””. He is one of the core developers of the scikit-learn machine learning library and has co-maintained it for several years.

His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize access to high-quality machine learning algorithms.

Introduction to Machine Learning with scikit-learn(Training)

Intermediate Machine Learning with scikit-learn(Training)

Advanced Machine Learning: Pipelines and Evaluation Metrics(Training)

Advanced Machine Learning with scikit-learn: Imbalanced Classification and Text Data(Training)

Senior Program ManagerMicrosoft

Faith Xu

Faith Xu is a Senior Program Manager at Microsoft on the Machine Learning Platform team, focusing on frameworks and tools. She leads efforts to enable efficient and performant productization of inferencing workflows for high volume Microsoft product and services through usage of ONNX and ONNX Runtime. She is an evangelist for the adoption of the open-source ONNX standard with community partners to promote an open ecosystem in AI.

From Research to Production: Performant Cross-platform ML/DNN Model Inferencing on Cloud and Edge with ONNX Runtime (Workshop)

Chief Data ScientistMonetate Labs

Austin Rochford

Austin Rochford is the Chief Data Scientist at Monetate. He is a recovering mathematician and is passionate about math education, Bayesian statistics, and machine learning. His writing is available online at austinrochford.com.

Data ScientistMicrosoft

Prabhat Roy

Prabhat Roy works as a Data and Applied Scientist at Microsoft, where he is one of the two main contributors to sklearn to onnx converter project (https://github.com/onnx/sklearn-onnx). In the past, he has contributed to ML.net, which is an open-source ML library for .net developers and worked with customers on text and image classification problems.

From Research to Production: Performant Cross-platform ML/DNN Model Inferencing on Cloud and Edge with ONNX Runtime(Workshop)

Senior Data ScientistMicrosoft

Xiaoyong Zhu

Xiaoyong Zhu is a Senior Data Scientist working in the Microsoft Cloud AI Platform group. His current focus is on building scalable deep learning algorithms and infrastructure.

Looking From Above: Object Detection And Other Computer Vision Tasks On Satellite Imagery(Talk)

 


Click Here For Full Lineup
2020 Speakers

Focus Area: ML for Programmers, MLOps & Data Engineering      Session: Talk 

Accelerate ML Lifecycle With Kubernetes and Containerized Data Science Tools

Abhinav Joshi, Sr. Principal Marketing Manager, Red Hat

Focus Area: ML for Programmers, Deep Learning      Session: Workshop 

From Research to Production: Performant Cross-platform ML/DNN Model Inferencing on Cloud and Edge With ONNX Runtime

Faith Xu, Senior Program Manager, Microsoft

Focus Area: ML for Programmers, Deep Learning      Session: Workshop 

From Research to Production: Performant Cross-platform ML/DNN Model Inferencing on Cloud and Edge With ONNX Runtime

Prabhat Roy, Data Scientist, Microsoft

Focus Area: ML for Programmers      Session: Talk 

Title Coming Soon!

Austin Rochford, Chief Data Scientist, Monetate Labs

Focus Area: ML for Programmers, MLOps & Data Engineering      Session: Workshop 

Title Coming Soon!

Dan Sullivan, PhD, AI and Cloud Architect & Author, New Relic, Inc | Wiley

What You'll Learn

Talks + Workshops + Special Events on these topics:

ML for Programmers Topics

  • What is AI Engineering 

  • Becoming an ML Programmer

  • Data Science at Scale 

  • Machine Learning for Engineers

  • Deep Learning for Engineers

  • Machine Vision and Autonomous Machines

  • NLP and Speech Recognition

  • and more…

Languages & Frameworks

  • Python SciPy, Pandas, PyMC3, etc

  • R Programming, Keras, CARET

  • Scikit-learn, PyTorch

  • Tensorflow, MXNet, Caffe 2.0, CNTK

  • Spark, MLlib, Storm, Hadoop, Mahout

  • Kubernetes, Kafka, Zeppelin, Ignite

  • Julia, Java, Jupyter Notebooks, NoSql, Neo4J

  • Julia, Java, Jupyter Notebooks, NoSql, Neo4J

You Will Meet

  • Some of the world’s leading AI experts

  • Some of the best minds and authors behind today’s most popular AI platforms

  • Artificial Ingelligence and data science innovators

  • Data science & analytics specialists

  • Developers, engineers and programmers looking to build AI enabled software

  • Hundreds of attendees focused on AI engineering

  • CTOs and Chief Data Scientists from startups and Fortune 500 companies

  • Data scientists, data engineers, and AI platform experts

  • Peers from startups to Fortune 500 companies wrestling with large sets of consumer data

  • Representatives from Government agencies, universities, and other large institutions

Previous Sessions on ML for Programmers Track

  • Workshop: Deciphering the Black Box: Latest Tools and Techniques for Interpretability

  • Talk: Adversarial Attacks on Deep Neural Networks

  • Training: Integrating Pandas with Scikit-Learn, an Exciting New Workflow

  • Workshop: Machine Learning for Digital Identity

  • Talk: Adding Context and Cognition to Modern NLP Techniques

  • Training: Good, Fast, Cheap: How to do Data Science with Missing Data

  • Workshop: Open Data Hub workshop on OpenShift

  • Talk: Practical AI solutions within healthcare and biotechnology

  • Training:  Apache Spark for Fast Data Science (and Fast Python Integration!) at Scale

  • Workshop: Reproducible Data Science Using Orbyter

  • Talk: Combining millions of products into one marketplace using computer vision and natural language processing

  • See the whole schedule!

Why Attend?

Immerse yourself in talks and workshops on AI Engineering frameworks, topics and languages

Learn about AI Engineering from leading AI experts who authored and built many of the platforms in use today

Network and connect with like-minded attendees to discover your next job, service, product or startup

Get speaker insights and training in AI frameworks such as TensorFlow, MXNet, PyTorch, Spark, Storm, Drill, Keras, and other AI platforms

Sign Up for ODSC EAST | April 13th – April 17th, 2020

Register Now
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