The stakes are higher than ever now for AI and security. Following Sepideh Seifzadeh's keynote on managing the AI lifecycle, Dawn Song of the University of California's BAIR Lab took the stage to discuss an important but often overlooked component of the AI lifecycle: Security, specifically with deep learning, and how the stakes are becoming higher as AI becomes more intelligent. We often hear about various security concerns in the news, seemingly every day in regards to a hack affecting our personal information. Though, now both the hackers themselves and AI systems are becoming significantly more sophisticated, and data scientists are tasked with finding new ways to mitigate, prevent, and remedy these advancements. "Our current framework is insufficient for protecting data rights and privacy," she said.

Every year, ODSC West gets hundreds of submissions from an array of incredibly talented data science practitioners. Those submissions offer a unique insight into what are some of the most important topics in data science right now. In this article, we'll outline just a few of these topics that our speakers will be presenting on at ODSC West October 29th - November 1st. Deepfakes: Identified as one of the major threats to governments, politicians, businesses, and private individuals alike, deepfakes–both innocent and malevolent–have been dominating the news for several months. Originally only known as a side effect of GANs, deepfakes can create images, videos, and voice files capable of deceiving, at least initially, the general public.

Editor's Note: Kirk will present his talk "Adapting Machine Learning Algorithms to Novel Use Cases" at ODSC West 2019. If there was a metric for success in the data science profession, it would require a multi-dimensional scoring model. This metric would cover a data scientist's technical skills and talents, analytic literacies and ways of thinking, and soft skills and aptitudes. Soft skills include a collection of aptitudes that I call the "seven C's of successful data scientists": Collaboration (data science as a team sport), Communication (data storytelling), Computational thinking, Critical thinking, Creativity, Curiosity, Continuous lifelong learning, Complex problem-solving, Compassion (design thinking), Consultative (active listening), Community-focused, and Cool under pressure ("tolerance for ambiguity"). Okay, that's more than seven things, but they represent my perspective on the journey to data science maturity as "sailing on the seven seas".

Renee Qian is an application engineer at MathWorks specializing in data analytics, machine/deep learning, and medical devices. She has an M.S. in biomedical engineering with a background in MR perfusion imaging of the brain. She joined MathWorks in 2012 as a technical support engineer being transferring to her current position in 2014.

Editor's Note: See Boris Kovalerchuk's talk "Interpretable Knowledge Discovery Reinforced by Visual Methods" at ODSC West 2019. Visual reasoning and discovery have a long history. Chinese and Indians had visual proof of the Pythagorean Theorem in 600 B.C. before it was known to the Greeks. Scientists such as Bohr, Boltzmann, Einstein, Faraday, Feynman, Heisenberg, Helmholtz, Herschel, Kekule, Maxwell, Poincare, Tesla, Watson, and Watt have declared the fundamental role that images played in their most creative thinking. The fundamental challenge for visual creative thinking and discovering in multidimensional data (n-D data) used in machine learning (ML) is that we cannot see multidimensional data with a naked eye.

Editor's note: Andras is a speaker for ODSC West 2019! Datasets are almost never complete and this can introduce various biases to your analysis. Due to these biases, your supervised machine learning model can produce incorrect predictions. The goal of this post is to give you an idea of why some of the most common approaches for dealing with missing values often introduce some type of bias. At ODSC West 2019, I will describe the methods and techniques that can help you to arrive at an unbiased conclusion in the face of missing data.

ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community. ODSC West 2019 is one of the largest applied data science conferences in the world. Our speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC West 2019 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.

ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community. ODSC West 2019 is one of the largest applied data science conferences in the world. Our speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC West 2019 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.