What we're about

Local community-ran meetup for developers interested in learning and practicing on AI, Machine Learning, Deep Learning, Data Science, and Cloud topics.

We will regularly invite tech leads from innovated companies, successful startups to share their practice experiences, best practices and deep dive on technology by tech talks, hands-on workshops, and bootcamps.

Due to the COVID-19, we host all events online, you can join from anywhere with zoom/youtube: https://learn.xnextcon.com

Upcoming events (3)

Ray Summit 2021 - Scaleble ML and Python (Free virtual conference)

** Register and attend: https://www.anyscale.com/ray-summit-2021?utm_source=aicamp&utm_medium=email&utm_campaign=raysummit
(rsvp on meetup was turned off)

This is a three-days, free virtual interactive event. Ray Summit brings together developers, AI&ML engineers, data scientists & architects to build scalable AI and machine learning systems. Topics include:
* Top AI and Machine Learning trends.
* ML in production & MLOps.
* Deep Learning & Reinforcement learning.
* End-to-End AutoML, Distributed XGBoost and Massive-scale ML.
* Building highly available & scalable application in the cloud
* Petabyte-Scale Data Lake
* Cloud computing, serverless & more.

Featured Speakers:
* Eric Brewer, Google Fellow and Professor Emeritus, UC Berkeley.
* Marvin Theimer, Distinguished Engineer, Amazon Web Services.
* Matt Johnson, Research Scientist, Google Brain.
* Dawn Song, Professor EECS, UC Berkeley.
* Sarah Bird, Principal Program Manager, Azure AI Microsoft.
* Sahika Genc, Principal Applied Scientist, Amazon AI.
* Michael Mui, Senior Software Engineer, Uber ML.
* Raghu Ganti, Principal Research Staff Member, IBM.
* Wei Chen, Deep Learning Software Engineer, NVIDIA.
* Edi Palencia, Principal AI Engineer, Microsoft.
* and 50 more

*** Details and RSVP: https://www.anyscale.com/ray-summit-2021?utm_source=aicamp&utm_medium=email&utm_campaign=raysummit

Session 2: workshop on summarize and find actionable insights from textual data

** Register and attend link: https://www.aicamp.ai/event/eventdetails/W2021063010

When you have a large collection of texts representing people’s opinions, such as product reviews, survey answers or social media, it is difficult to understand the key issues that come up in the data. Existing automated approaches are often limited to identifying recurring phrases or concepts and the overall sentiment toward them, but do not provide detailed or actionable insights.
In this workshop, we will show how to use Project Debater Early Access Program services for analyzing and deriving insights from answers to open-ended question. As an example, we will use Project Debater to analyze a collection of comments, from a community survey conducted in the city of Austin, and summarize it as a small set of key points

IBM AI tech talk series.
* Session 1 (June 16th): Project Debater- From an AI debating system to business applications (link: https://www.aicamp.ai/event/eventdetails/W2021061610 )

AI course: ML for Developers with Scikit-Learn (Cohort 5)

Online event

Paid online live course (using zoom), follow instructions below to enroll.
4-weeks AI course: ML for Developers with Scikit-Learn (Cohort 5)
Start date: July 13th,2PM~4PM PDT (Pacific time, GMT-7), Every Tue/Thu.

*** Enrollment Instructions*****
Enrollment link: https://www.aicamp.ai/course/coursedetails/C2021051814

In the AICamp online classroom (powered by Zoom), we will meet once 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/ 16 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

In this course you will learn the fundamentals of machine learning including intuitions, important theoretical aspects and how to use machine learning algorithms to solve problems. Students will learn about the foundational underpinnings of machine learning as well as how to put that knowledge to the test with practical exercises.

The course takes projects focused approach to teach you machine learning by building machine learning models and projects. 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.

The course balances learning theory, coding exercises, and working on projects. Students who take this course will be able to:
* Identify and frame problems that can be solved by machine learning
* Choose the right techniques to the problems
* Understand key machine learning concepts and how algorithms / models work
* Build and training various models with scikit-learn
* Troubleshoot and improve models

*** Enrollment Instructions*****
Enrollment link: https://www.aicamp.ai/course/coursedetails/C2021051814

Past events (70)

Photos (60)