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Upcoming events (3)
Paid online live course (using zoom), follow instructions below to enroll ----------- 4-weeks AI course: Full Stack Machine Learning on GCP (Cohort 10) Start date: Jan 18th，10AM~11:30AM PST, Every Mon&Wed. Enrollment: https://learn.xnextcon.com/course/coursedetails/C2021011810 ** 30% off promotion price will end soon. In the AICamp online classroom (powered by Zoom), we will meet twice a week and you will interact with instructors and other classmates, listen the lectures, discuss problems; After class, you will work on projects, homework, and get support on private group on slack. The course include: * 4 weeks/ 8 sessions/ 12 hours * 8 lectures / 8 hands-on projects * Live Sessions, Real time interaction * Capstone projects, work with peer students globally * Slack supports to projects and homework * Students project demonstration, add to Github portfolio * Earn certificate upon course completion * Free trial, and scholarship is available Details: In this course, we will train you to become a Full Stack Machine Learning Engineer, capable of not just training models but also deploying and managing them in production for business value. You will learn machine learning primarily through building 8 production grade services, step by step. You will learn how to build production AI on GCP (Google Cloud Platform), how to integrate it with an application, and how to manage it through its lifecycle. You will also build from scratch a custom project (where you will gather data, train and tune a production grade models, build a prediction service, and connect that prediction service to create your own ML application).
Free online AI tech talk event, Join from anywhere with zoom, Register and attend: https://learn.xnextcon.com/event/eventdetails/W2021011911 Agenda: * pre-event networking (20mins) * community updates, jobs/interns/talents announcements. (5mins) * tech talk and Q&A (45mins) * Raffle for the 5 copies of the O’Reilly book (Machine Learning Design Patterns, https://www.oreilly.com/library/view/machine-learning-design/9781098115777/) Abstract: Design patterns capture best practices and solutions to recurring problems. Join us for the tech talks and AMA (Ask Me Anything), by the authors of the newly released O’Reilly book “Machine Learning Design Patterns”, covering solutions to common challenges in Data Preparation, Model Building, and MLOps. Lak, Sara and Michael will introduce three of these tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. They will discuss the pattern: a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. Talk #1: Data Representation Design Pattern: Embeddings, by Valliappa Lakshmanan Talk #2: Reproducibility Design Pattern: Model Versioning, by Sara Robinson Talk #3: Problem Representation Design Pattern: Multilabel, by Michael Munn We will also raffle for 5 copies of the book (for winners, hard copy ship to you if you are within US, e-copy if you are outside of US).
Free online AI tech talk event, you can join from anywhere with zoom, Register and attend: https://learn.xnextcon.com/event/eventdetails/W2021011210 Agenda: * pre-event networking (20mins) * community updates, jobs/interns/talents announcements. (5mins) * tech talk and Q&A (45mins) Abstract: In this tech talk, we’ll discuss how the data scientists from Amazon ML Solutions Lab selected important features and used XGBoost in Amazon SageMaker to help football coaches to gain insights and prepare games better. We’ll discuss the methodology we used in details and provide code examples of model training in Amazon SageMaker. This model is customized for UIUC’s football team and their opponents, and will help UIUC’s coaches prepare for more scenarios in upcoming seasons. Additionally, it will help players react correctly and quickly to game situations.