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When it comes to moving people and making deliveries, few companies are more widely spread and more widely recognized than Uber. Uber is part of the logistics fabric of more than 700 cities around the world, and whether it's a ride, a sandwich, or a package, they use technology to give people what they want, when they want it. Uber spends hundreds of millions of dollars in acquisition and retention and we are constantly optimizing the allocation of these budgets and performing experimentation. We use AI in creative ways to: - Improve the signal on A\B experiments and have better reads and insights - Advanced segmentation of customers by propensity to act, churn, open an email - Cross sell predictions - Models of resurrection and reactivation - Natural Language to provide insights on content - Loyalty programs In this talk, I will discuss how predictive models are used across these areas: - How to think and interpret predictive models - What metrics we use to evaluate these models - The tools and technologies we use - Specific case studies in optimization, channel attribution Agenda: 5:50 pm - 6:00 pm Arrival and socializing 6:00 pm - 6:10 pm Opening words 6:10 pm - 7:10 pm Mario Vinasco, "Marketing Analytics and Predictive Modeling with AI" 7:10 pm - 7:30 pm Q&A About Mario Vinasco: Mario Vinasco has over 15 years of progressive experience in data driven analytics with emphasis in database programming and machine learning creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment. Mario specializes in developing and applying leading edge business analytics to complex business problems using big data and predictive modeling platforms. Mario holds a Masters in engineering economics from Stanford University and currently manages a team of data science at Uber Technologies responsible for customer management, retention and prediction. The team conducts advanced segmentation of customers by propensity to act, churn, open email and set up sophisticated experiments to test and validate hypothesis. Until recently, Mario worked for Facebook as data scientist in the consumer marketing group; in this role he was responsible for improving the effectiveness of Facebook’s own consumer-facing campaigns. Key projects included ad-effectiveness measurement of Facebook’s brand marketing activities, and product campaigns for key product priorities using advanced experimentation techniques. Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.
This is a great opportunity to jump into a data science career. We are offering a boot camp to prepare you a data analyst position. This boot camp is for non-coders who are interested in learning data science or those who have a technical background although are not familiar with the fundamentals of data science. The course will teach you the fundamental skills of Python, SQL, Statistics and an introduction to machine learning. During our course, you will explore a hands-on experience that will ignite your enthusiasm and confidence to learn data analytics. Visit our website to learn detailed information about this boot camp. https://magnimindacademy.com/all-courses/data-science-prep/ Fee: Data Analysis with Python Course has a $599 tuition fee. For the “Super Early Bird” applicants (August 27 – September 9) the tuition fee is $399. For our “Early Bird” applicants (September 10 – September 17), the tuition fee is $499. Schedule: September 22 – 29 and October 6 – 13 Sundays, from 9:00 am to 2:00 pm What You’ll Learn in these 20 hours? 1- Python Explore fundamental data types such as strings, booleans, lists, and dictionaries. Learn how to create and organize your code into a clean and professional flow. Learn to analyze data and grow skills to become a data analyst. 2- SQL Discover how databases are structured, how to add and remove data from a database, and how to query a database, as well as, answer questions using aggregations and joins. 3- Probability and Statistics Model real data using common probability distributions and learn how to infer properties during the data generating process. 4- Data Visualization Most importantly, explore python libraries, tools, Pandas, Numpy, and Matplotlib. Application: We have 20 people attendee limit for this mini boot camp. You can apply through Eventbrite, https://www.eventbrite.com/e/data-analysis-with-python-4-days-20-hours-tickets-70546970889 or, our website to apply and pay. https://magnimindacademy.com/all-courses/data-science-prep/
We are expanding to offer a Bootcamp on Machine Learning Interview tactics and training. You don’t want to miss this opportunity especially if you have been preparing for interviews for Machine Learning Engineering jobs and would like to stand out from the crowd. This Bootcamp will be given by the talented Google Engineer, Osman Aka, who immerses himself in machine learning training. We will cover several interview questions at various levels. It will be interactive and you will have a great sense of actual interview questions and different approaches for answering them. You will have guidance from our mentors and participate in mock interviews which you will receive valuable feedback from at the end of the Bootcamp. Make your first impression your best impression at every interview! Visit our website to learn detailed information about this boot camp. https://magnimindacademy.com/all-courses/machine-learning-interview-tactics-mini-bootcamp/ Fee: Our Machine Learning Interview Tactics Mini Bootcamp has a $599 tuition fee. For the “Super Early Bird” applicants (September 17 – September 23) the tuition fee is $399. For our “Early Bird” applicants (September 24 – September 30), the tuition fee is $499. Schedule: October 7 – 14 – 21 – 28 Mondays, from 6:30 pm to 9:30 pm Application: We have 20 people attendee limit for this mini boot camp. You can apply through Eventbrite, https://www.eventbrite.com/e/machine-learning-interview-tactics-mini-bootcamp-4-days-12-hours-tickets-73122020933 or, our website to apply and pay. https://magnimindacademy.com/all-courses/machine-learning-interview-tactics-mini-bootcamp/
We have another exciting AI meetup. Our speaker Aaron Edell says that: After selling my machine learning startup Machine Box to Veritone, Inc. in 2018, I've had a chance to reflect, research, and experience where and how businesses are spending their money on ML. This talk is to share my experience navigating the business of applied machine learning, where we saw the most adoption and financial success, and where I would turn my attention to next. Agenda: 5:50 pm - 6:00 pm Arrival and socializing 6:00 pm - 6:10 pm Opening words 6:10 pm - 7:10 pm Aaron Edell, "Future of AI" 7:10 pm - 7:30 pm Q&A About Aaron Edell: Aaron Edell is a veteran speaker and writer on the topics of machine learning, metadata, and content management. He was the co-founder and CEO of Machine Box, Inc., an award-winning startup that builds production-ready machine learning models that anyone can integrate, deploy and scale which was acquired by Veritone in September of 2018. Previously, he helped found and grow Graymeta, Inc., a machine learning and metadata company. Prior to that Edell was at Oracle, Front Porch Digital, Neulion, and SAMMA Systems in various roles from senior solutions architect to product manager. Aaron has published papers on metadata and machine learning and consulted major media and entertainment companies on content management since 2005.