What we're about
Upcoming events (3)
This is online tech event, you can join from anywhere with zoom, please register and attend here: https://learn.xnextcon.com/event/eventdetails/W20081209 Social networking with speakers, attendees 30mins before/after the event on slack. Join slack by the invitation: https://bit.ly/3gi7bjf . The two channels: #jobs for job posting from speakers, partners, sponsors companies, and you can Q&A with hiring managers right in the channel. #events for events Q&A, mixing and networking with speakers and other peer attendees. Snakebite is the most deadly neglected tropical disease (NTD), being responsible for a dramatic humanitarian crisis in global health. Snakebite causes over 100,000 human deaths and 400,000 victims of disability and disfigurement globally every year. Antivenoms can be life‐saving when correctly administered but this often depends on the correct taxonomic identification (i.e. family, genus, species) of the biting snake. Can deep learning provide these rural communities in developing countries with a solution? This talk will focus on lessons learned from AIcrowd Ai4Good competition "Snake Species Identification Challenge" and provide a step-by-step guide for beginners who wish to get started in the fascinating universe of data science competitions.
This is free online event, you can join from anywhere with zoom. meetup registration is turned off. please register: https://www.eventbrite.com/e/mlops-global-summit-2020-tickets-114782351102 =========== MLOps Global Summit 2020 (Virtual) Running machine learning in production is hard and complex tasks, with new challenges in managing models and pipeline services. The event brings industry experts and tech leads from global to share practical experiences, best practices and tools/frameworks on manage machine learning in production through its lifecycle, which involves deployment, experiments at scale, versioning, monitoring, troubleshooting and more. This one-day, 20 hours, interactive event features a blend of deep dive tech talks, hands-on workshops and networking opportunities with like minded developers from all over the world. The previous events had 1,000+ developers joined from 50+ countries Website: http://mlops20.xnextcon.com Date/Time: The event is 20 hours, have two blocks for attendees in different time zones: * Block 1: for North America Region: 10am~4pm PST (GMT-7) * Block 2: for Europe/Africa/Middle East region: 9am ~ 3pm BST (GMT+1) India, Asia Pacific, Australia region: 1:30pm ~ 6:30 IST (GMT+5.30), 4pm-9pm SGT (GMT+8), 6pm-11pm AEST (GMT+10)
This is paid online course, follow instructions below to enroll ----------- We are starting new batch of this popular live course: 4-week AI course: Deep Learning for Developers. This course is online live course with zoom. You can listen, watch, interact, Q&A with instructors. If you miss the live session due to time zone or conflict, you can learn session replay with recordings, course materials any time. Start date: 24 Aug, 5pm PT (US pacific time, GMT-7, check your local time zone). Every Monday and Wednesday. * 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 Enrollment: https://learn.xnextcon.com/course/coursedetails/C20082417 Details: learn deep learning by building deep learning models and projects. The course takes unique project focused approach to teach you deep learning by building deep learning models. The instructor will walk you through a series of curated projects, and explain the key concepts as they arise. Students will learn the theory and how these models work under the hood while writing code, and building neural networks. Students who take this course will be able to: * Identify and frame problems that can be solved by deep learning * Choose the right techniques to the problems * Understand key deep learning concepts and how deep learning models work * Identify and fix problems with messy datasets * Build deep neural nets for classification and regression using the Keras framework * Build convolutional neural networks for image classification, object localization and segmentation using the Keras * Discuss the parts and processes involved in building large scale deep learning applications