What we're about

Welcome to the group. We’re excited to bring you the latest and practical technology on AI, Machine Learning, Deep Learning, Data Science and Big Data.

Our goal is to congregate with AI enthusiasts from all over Sydney to learn and practice AI tech, through tech talks, study jams, code labs etc.. we regularly invite tech leads from innovated companies, successful startups to share their practice experiences and practices in the world of AI, Cloud, Data, Blockchain.

If you’d like to speak at future meetups, co-promote your meetup or inquire about partnership opportunities, please feel free to reach out to us

===Tentative Agenda =====

5:30pm - 5:50pm, Snack & social
5:50pm - 6:00pm, Intro/announcement
6:00pm - 7:00pm, Tech Talk 1 and Q&A
7:00pm - 8:00pm, Tech Talk 2 and Q&A
8:00pm - 8:30pm, Mingle

Upcoming events (3)

live crash course - Best practices for machine learning engineers

This is online crash course gets you up to practice Machine Learning including: Setting expectations for machine learning,Tools of the trade (Python, R, TensorFlow, PyTorch, Jupter, Notebooks, etc.),Training and inference characteristics (memory, batch latency,throughput, etc.),etc…. *you can listen, watch, Q&A with speakers from anywhere around the world. * 32 topics in 8 hours (4 sessions and 2 hours/session). *Real-time interactions with instructors, Watch recorded videos any time after. *code labs, projects, and real-time discussion/Q&A on Slack group Sign up: https://learn.xnextcon.com/course/coursedetails/C19021216 Description: Machine learning is a complex field that spans mathematics, software, and computer systems. How do engineers work effectively with data scientists in building next generation applications with machine learning? What is the most effective way to deliver consistent value? What are common mistakes to avoid? In this course, we present a set of best practices for software and systems engineers that can be applied to machine learning application development. The course covers the full gamut of required knowledge, ranging from software tools, model selection, and infrastructure to deployment and quality assurance processes. COURSE SCHEDULE: * Session 1: Feb. 12th Tue 4pm-6pm PST * Session 2: Feb. 14th Thu 4pm-6pm PST * Session 3: Feb. 19th Tue 4pm-6pm PST * Session 4: Feb. 21st Thu 4pm-6pm PST Speaker/instructor:Garrett Smith,creator of Guild AI Sean Ma,research manager For more online AI tech talks, courses, bootcamps : https://learn.xnextcon.com

live crash course - Best practices for machine learning engineers

This is online crash course gets you up to practice Machine Learning including: Setting expectations for machine learning,Tools of the trade (Python, R, TensorFlow, PyTorch, Jupter, Notebooks, etc.),Training and inference characteristics (memory, batch latency,throughput, etc.),etc…. *you can listen, watch, Q&A with speakers from anywhere around the world. * 32 topics in 8 hours (4 sessions and 2 hours/session). *Real-time interactions with instructors, Watch recorded videos any time after. *code labs, projects, and real-time discussion/Q&A on Slack group Sign up: https://learn.xnextcon.com/course/coursedetails/C19021216 Description: Machine learning is a complex field that spans mathematics, software, and computer systems. How do engineers work effectively with data scientists in building next generation applications with machine learning? What is the most effective way to deliver consistent value? What are common mistakes to avoid? In this course, we present a set of best practices for software and systems engineers that can be applied to machine learning application development. The course covers the full gamut of required knowledge, ranging from software tools, model selection, and infrastructure to deployment and quality assurance processes. COURSE SCHEDULE: * Session 1: Feb. 12th Tue 4pm-6pm PST * Session 2: Feb. 14th Thu 4pm-6pm PST * Session 3: Feb. 19th Tue 4pm-6pm PST * Session 4: Feb. 21st Thu 4pm-6pm PST Speaker/instructor:Garrett Smith,creator of Guild AI Sean Ma,research manager For more online AI tech talks, courses, bootcamps : https://learn.xnextcon.com

online hands-on workshop: Dimension reduction: from modeling to visualization

This is online hands-on workshop, with multiple sessions. the time is at US pacific timezone, please check the website for details: https://learn.xnextcon.com/course/coursedetails/C19030510 In this workshop, you will learn about widely used dimension reduction methods such as PCA, ICA, t-SNE, and UMAP. You will learn how to explore them to reduce dimensionality of your data in Python, how to use methods like PCA in supervised learning schemes and how to improve your reports using visualization techniques like t- SNE. This will be a hands on workshop in which we will work on multiple datasets and will learn how to implement each one of the aforementioned methods on them in Python *you can listen, watch, Q&A with speakers from anywhere around the world. * 8 topics in 4 hours (2 sessions and 2 hours/session). *Real-time interactions with instructors, Watch recorded videos any time after. *code labs, projects, and real-time discussion/Q&A on Slack group COURSE SCHEDULE: *Session 1: Mar. 5th Tue 10am-12pm PST *Session 2: Mar. 7th Thu 10am-12pm PST For more online AI tech talks, courses, bootcamps :https://learn.xnextcon.com

Past events (7)