Jon Krohn is Chief Data Scientist at the machine learning company untapt. He authored the book Deep Learning Illustrated, which was released by Addison-Wesley in 2019 and became an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University, New York University, and the NYC Data Science Academy, as well as online via O’Reilly, YouTube, and his A4N podcast on A.I. news. Jon holds a doctorate in neuroscience from Oxford and has been publishing on machine learning in leading academic journals since 2010.
Hannah Arnson serves as Director of Data Science with Pandata – a Cleveland-based AI consulting firm. There, she leverages her 10+ years of experience to lead AI solution design and development, with a focus on ethical and approachable AI. Hannah began her career as a neuroscientist, receiving a Ph.D. in neuroscience from Washington University in St. Louis, then continuing on to do postdoctoral research. During this time, she developed statistical and mathematical models to better understand topics ranging from the sense of smell to navigation in pigeons. As a data scientist, Hannah’s passions lie in finding patterns within complex datasets and educating to make these technical concepts accessible to all.
Thomas J. Fan is a Staff Associate at the Data Science Institute at Columbia University. He is one of the core developers of scikit-learn, an open source machine learning library written in Python. Thomas holds a Masters in Mathematics from NYU and Masters in Physics from Stony Brook University. He also maintains skorch, a scikit-learn compatible neural network library that wraps PyTorch. He believes that developing open source software is one of the best ways to maximize one’s impact.
Introduction to Scikit-learn: Machine Learning in Python(Half-Day Training)
Danielle Aring is an IT Security Data Engineer IV with the Transmission Security Operations Center (TSOC) at FirstEnergy. In her role, she is responsible for the design, development, implementation and maintenance of IT security equipment and software. Danielle holds a master’s in Computer Information Science from Cleveland State University. With an extensive background in software engineering and expertise in machine learning, Danielle is guiding the transition of the TSOC away from reactionary, rules-based threat detection to preventative, predictive, threat-hunting approaches. She built her organizations’ security data lake in Hadoop from the ground up. Developed several large-scale data pipelines for near real-time security log ingest along with alerting, monitoring and metrics. Danielle is passionate about cybersecurity educational awareness and innovative applications of AI/ML to the changing threat landscape.
Dr. Kirk Borne is the Principal Data Scientist and an Executive Advisor at global technology and consulting firm Booz Allen Hamilton. In those roles, he focuses on applications of data science, data management, machine learning, A.I., and modeling across a wide variety of disciplines. He also provides training and mentoring to executives and data scientists within numerous external organizations, industries, agencies, and partners in the use of large data repositories and machine learning for discovery, decision support, and innovation. Previously, he was Professor of Astrophysics and Computational Science at George Mason University for 12 years where he did research, taught, and advised students in data science. Prior to that, Kirk spent nearly 20 years supporting data systems activities on NASA space science programs, which included a period as NASA’s Data Archive Project Scientist for the Hubble Space Telescope. Dr. Borne has a B.S. degree in Physics from LSU, and a Ph.D. in Astronomy from Caltech. In 2016 he was elected Fellow of the International Astrostatistics Association for his lifelong contributions to big data research in astronomy. As a global speaker, he has given hundreds of invited talks worldwide, including conference keynote presentations at many dozens of data science, A.I. and big data analytics events globally. He is an active contributor on social media, where he has been named consistently among the top worldwide influencers in big data and data science since 2013. He was recently identified as the #1 digital influencer worldwide for 2018-2019. You can follow him on Twitter at @KirkDBorne.
Atypical Applications of Typical Machine Learning Algorithms(Half-Day Training)
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
Organizations are now understanding the need to break down big data to make it intuitive, insightful, and actionable. Be among the first to understand the power of ml for cybersecurity
Immerse yourself in two days of in-depth talks and workshops on data visualization and data science topics, tools, and languages.
Get full access to the full suite of recorded presentations on-demand post conference.
With an incredible lineup, this event will provide the training and insight for professionals who understand their organization’s need to deliver compelling data science solutions
Get access to the Open Data Visualization Conference plus 5 other co-located conferences including open data science, big data science, and disruptive data science.
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