Dr. Jennifer Prendki is the founder and CEO of Alectio, the first startup fully focused on DataPrepOps. She and her team are on a fundamental mission to help ML teams build models with less data. Before Alectio, Jennifer was the Vice President of ML at Figure Eight. She also built an entire ML function from scratch at Atlassian and led multiple Data Science projects on the Search team at Walmart Labs. She is recognized as one of the top industry experts on Active Learning and ML lifecycle management. She is an accomplished speaker who enjoys addressing both technical and non-technical audiences.
Datacast Episode 42: Privacy-Preserving NLP with Patricia Thaine
Patricia Thaine is a Computer Science Ph.D. Candidate at the University of Toronto and a Postgraduate Affiliate at the Vector Institute researching privacy-preserving natural language processing, with a focus on applied cryptography. Her research interests also include computational methods for lost language decipherment.
She is the Co-Founder and CEO of Private AI, a Toronto- and Berlin-based startup creating a suite of privacy tools that make it easy to comply with data protection regulations, mitigate cybersecurity threats, and maintain customer trust.
Datacast Episode 37: Machine Learning In Production with Luigi Patruno
Luigi Patruno is a Data Scientist and the Founder of MLinProduction.com. He’s currently the Director of Data Science at 2U, where he leads a team of data scientists and ML engineers in developing machine learning models and infrastructure to predict student success outcomes. Luigi founded MLinProduction.com to educate data scientists, ML engineers, and ML product managers about best practices for running machine learning systems in production.
As a consultant for Fortune 500s and start-ups, Luigi helps companies utilize data science to create competitive advantages. He has taught graduate-level courses in Statistics and Big Data Engineering and holds a Masters in Computer Science and a BS in Mathematics.
Datacast Episode 36: Machine Learning Bookcamp with Alexey Grigorev
Alexey Grigorev lives in Berlin with his wife and son. He’s a software engineer with a focus on machine learning, currently working at OLX Group as a Lead Data Scientist. Alexey is a Kaggle master, and he wrote a couple of books. One of them is “Mastering Java for Data Science,” and now he’s working on another one — “Machine Learning Bookcamp.”
Datacast Episode 34: Deep Learning Generalization, Representation, and Abstraction with Ari Morcos
Ari Morcos is a Research Scientist at Facebook AI Research working on understanding the mechanisms underlying neural network computation and function and using these insights to build machine learning systems more intelligently. In particular, Ari has worked on a variety of topics, including understanding the lottery ticket hypothesis, the mechanisms underlying common regularizers, and the properties predictive of generalization, as well as methods to compare representations across networks, the role of single units in computation, and on strategies to measure abstraction in neural network representations.
Previously, he worked at DeepMind in London, and earned his Ph.D. in Neurobiology at Harvard University, using machine learning to study the cortical dynamics underlying evidence accumulation for decision-making.
Datacast Episode 32: Economics, Data For Good, and AI Research with Sara Hooker
Sara Hooker is a researcher at Google Brain doing deep learning research on reliable explanations of model predictions for black-box models. Her main research interests gravitate towards interpretability, model compression, and security. In 2014, she founded Delta Analytics, a non-profit dedicated to bringing technical capacity to help non-profits across the world use machine learning for good. She grew up in Africa, in Mozambique, Lesotho, Swaziland, South Africa, and Kenya. Her family now lives in Monrovia, Liberia.
Datacast Episode 30: Data Science Evangelism with Parul Pandey
Parul Pandey is a Data Science Evangelist at H2O.ai. She combines Data Science, evangelism and community in her work. Her emphasis is to break down the data science jargon for the people. Prior to H2O.ai, she worked with Tata Power India, applying Machine Learning and Analytics to solve the pressing problem of load sheddings in India. She is also an active writer and speaker and has contributed to various national and international publications including Towards Data Science, Analytics Vidhya, and KDNuggets and Datacamp.
Datacast Episode 29: From Bioinformatics to Natural Language Processing with Leonard Apeltsin
Dr. Leonard Apeltsin is a research fellow at the Berkeley Institute for Data Science. He holds a Ph.D. in Biomedical Informatics from UCSF and a BS in Biology and Computer Science from Carnegie Mellon University. Leonard was a Senior Data Scientist & Engineering Lead at Primer AI, a machine learning company that specializes in using advanced Natural Language Processing Techniques to analyze terabytes of unstructured text data. As a founding team-member, Leonard helped expand the Primer AI team from four employees to over 80 people. Outside of Data Science and ML, Leonard enjoys scuba diving, salsa dancing, and making short documentary films.
Datacast Episode 28: Excelling in Data Analytics with Vincent Tatan
Vincent Tatan is a Data and Technology enthusiast with relevant working experiences from Google LLC, Visa Inc., and Lazada to implement microservice architectures, business intelligence, and analytics pipeline projects. Vincent is a native Indonesian with a record of accomplishments in problem-solving with strengths in Full Stack Development, Data Analytics, and Strategic Planning. He has been actively consulting Singapore Management University’s Business Intelligence and Analytics Club, guiding aspiring data scientists and engineers from various backgrounds and opening up his expertise for businesses to develop their products. Vincent also opens up his one on one mentorship service to coach on landing your dream Data Analyst/Engineer Job at Google, Visa, or other large tech companies.
Datacast Episode 27: Feature Engineering with Ben Fowler
Ben Fowler has been in the field of data science for over five years. In his current role at Southeast Toyota Finance, Ben leads the end to end model development process to solve the problem of interest. Ben holds a Master of Science in Data Science from Southern Methodist University, graduating in 2017. Following graduation, Ben has been a guest speaker to the SMU program multiple times. Additionally, Ben has spoken at the PyData Miami 2019 and PyData LA 2019 Conferences and has spoken multiple times at the West Palm Beach Data Science Meetup.