Boston | April 14th – April 17th, 2020

Machine Learning & Deep Learning Track

Learn the latest models, advancements, and trends from the top practitioners behind two of data science’s hottest topics

Comprising multiple tracks, this focus area is where leading experts in the rapidly expanding fields of Deep Learning and Machine Learning gather to discuss the latest advances, trends, and models in this exciting field.

Attend talks, tutorials, and workshops and hear from the creators and top practitioners as they teach the latest models and trends in Machine Learning and Deep Learning to solve problems in business and society. Some of the topics you’ll learn include:

  • Machine Learning

  • Deep Learning

  • Deep Reinforcement Learning

  • Neural Networks

  • LSTM, CNNs, RNNs, & GANs,

  • Computer Vision

  • Pattern Recognition

  • Tensorflow

  • Scikit-learn

  • Keras

  • Caffe 2

  • PyTorch

  • Theano

  • Apache Spark & MlLib

  • and many more…

  • Federated Learning

  • Transfer Learning

  • Autonomous Machines

  • MLOps and Kubeflow

  • Recommendation Systems

  • Never Ending Learning for ML

  • Causal Inference

Some Current ML & DL Speakers


Click Here For Full Lineup
2020 Speakers

Sample Talk, Workshop, and Training Sessions

Machine Learning & Deep Learning Sessions
Friday, April 17th
Tuesday, April 14th
Wednesday, April 15th
Friday, April 17th
Tuesday, April 14th
Wednesday, April 15th
09:00 - 18:00
Understanding the PyTorch Framework with Applications to Deep Learning

Training | Deep Learning | Beginner

 

Over the past couple of years, PyTorch has been increasing in popularity in the Deep Learning community. What was initially a tool used by Deep Learning researchers has been making headway in industry settings. In this session, we will cover how to create Deep Neural Networks using the PyTorch framework on a variety of examples. The material will range from beginner – understanding what is going on “under the hood”, coding the layers of our networks, and implementing backpropagation – to more advanced material on RNNs, CNNs, LSTMs, & GANs. Attendees will leave with a better understanding of the PyTorch framework. Furthermore, a link to a clean documented GitHub repo with the solutions of the examples covered will be provided…more details

Understanding the PyTorch Framework with Applications to Deep Learning image
Robert Alvarez, PhD
Head of Data Science | Podium Education
Session Title by Andreas Mueller Coming Soon!

Training

Session Title by Andreas Mueller Coming Soon! image
Andreas Mueller, PhD
Author, Research Scientist, Core Contributor of scikit-learn | Columbia Data Science Institute
Session Title by Dr. Jon Krohn Comoing Soon!

Training

Session Title by Dr. Jon Krohn Comoing Soon! image
Dr. Jon Krohn
Chief Data Scientist, Author of Deep Learning Illustrated | Untapt
11:30 - 12:15
Machine Learning and Artificial Intelligence in 2020: Recent Trends, Technologies, and Challenges

Talk | Machine Learning | Intermediate

 

Not even a decade ago, machine learning was a profession for an elite few. Nowadays, we don’t have to be math or engineering wizards to implement state-of-the-art predictive models. Advances in computing hardware, and especially the utilization of GPUs for training deep neural networks, make it feasible to develop predictive models that achieve human-level performance in various natural language processing and image recognition challenges. The manifold software layers and APIs that are allowing us to utilize these hardware resources are becoming ever so convenient. In this talk, I will highlight the research and technology advances and trends of the last year(s), concerning GPU-accelerated machine learning and deep learning, and focusing on the most profound hardware and software paradigms that have enabled it…more details

Machine Learning and Artificial Intelligence in 2020: Recent Trends, Technologies, and Challenges image
Sebastian Raschka, PhD
Professor, Researcher, Author of 'Python Machine Learning' | University of Wisconsin-Madison
Session Title by Faith Xu and Prabhat Roy Coming Soon!

Workshop

Session Title by Faith Xu and Prabhat Roy Coming Soon! image
Faith Xu
Senior Program Manager | Microsoft
Session Title by Faith Xu and Prabhat Roy Coming Soon! image
Prabhat Roy
Data Scientist | Microsoft
13:00 - 16:00
Adapting Machine Learning Algorithms to Novel Use Cases

Training | Machine Learning | Intermediate

 

How can an idea from an 18th-century Presbyterian minister be used to estimate the mass density function of galaxies across the Universe? How can a marketing segmentation algorithm protect astronauts traveling to Mars from certain death? How does a Formula 1 race from then 1950’s inspire one of the greatest data science use cases for the Internet of Things? How can a violation of the triangle inequality theorem in mathematics lead to a cure for cancer? This workshop will answer these questions, and more, by presenting several examples of one of the key aptitudes of successful data science practice, which is adaptability. In particular, I will present several well-known algorithms (including some that we would not even call “algorithms”) that may have been adopted for specific use cases or applied in specific business domains, and then I will show how each one can be adapted to a novel use case that may be less obvious, perhaps producing significantly surprising results in some other domain. Plus, I will suggest some new opportunities that may come from interesting combinations of data and algorithms. The point of these exercises is to demonstrate how data scientists can create even more value, beyond that which is expected, from our data assets and our algorithmic talents…more details

Adapting Machine Learning Algorithms to Novel Use Cases image
Dr. Kirk Borne
Principal Data Scientist | Booz Allen Hamilton
Session Title by Andreas Mueller Coming Soon!

Training

Session Title by Andreas Mueller Coming Soon! image
Andreas Mueller, PhD
Author, Research Scientist, Core Contributor of scikit-learn | Columbia Data Science Institute
13:01 - 16:00
Machine Learning for Trading

Training | Machine Learning | Open-source | Beginner-Intermediate

 

The rapid progress in machine learning (ML) and the massive increase in the availability and diversity of data has enabled novel approaches to quantitative investment. It has also increased the demand for the application of data science to develop both discretionary and algorithmic trading strategies.
In this workshop, we will cover popular use cases for ML in the investment industry, and how data science and ML fit into the workflow of developing a trading and investment strategy from the identification and combination of alpha factors to strategy backtesting and asset allocation.
The workshop uses Python and various standard data science and machine learning libraries like pandas, scikit-learn, gensim, spaCy as well as TensorFlow and Keras. The code examples will be presented using jupyter notebooks and are based on my book ‘Machine Learning for Algorithmic Trading’…more details

Machine Learning for Trading image
Stefan Jansen
Founder & Lead Data Scientist | Applied Artificial Intelligence
Select date to see events.

See all our talks and hands-on workshop and training sessions
See all sessions

You Will Meet


  • Top speakers and practitioners in Machine Learning and Deep Learning

  • Data Scientists and Data Analysts

  • Decision makers

  • Software Developers focused on Machine Learning and Deep Learning

  • Data Science Innovators

  • CEOs, CTOs, CIOs

  • Industry leaders

  • Core contributors in the fields of Machine Learning and Deep Learning

  • Data Science Enthusiasts

Why Attend?


Immerse yourself in talks, tutorials, and workshops on Machine Learning and Deep Learning tools, topics, models and advanced trends

Expand your network and connect with like-minded attendees to discover how Machine Learning and Deep Learning knowledge can transform not only your data models but also your business and career

Meet and connect with the core contributors and top practitioners in the expanding and exciting fields of Machine Learning and Deep Learning

Learn how the rapid rise of intelligent machines is revolutionizing how we make sense of data in the real world and its coming impact on the domains of business, society, healthcare, finance, manufacturing, and more

Sessions on Machine Learning & Deep Learning 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!

Sign Up for ODSC EAST 2020 | April 14th – April 17th

Register Now