What we're about
Upcoming events (3)
This is online live course (using Zoom), follow instructions below to enroll
4-weeks AI course: Deep Learning for NLP with PyTorch (Cohort 3)
Start date: May 10th，11AM PDT (GMT-7), Every Mon/Wed.
** 50% off promotion price will end on Apr 28.
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/ 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
* Earn certificate upon course completion
Natural Language Processing (NLP) is the fastest-growing field of deep learning with interest and funding from top AI companies to solve problems of language, text, and unstructured information. This has resulted in a tremendous focus on model building that combines language, mathematics, and computer science.
This 4-weeks course will focus on problems of text summarization, question answering, and sentiment classification using modern approaches to model-building (GNMT, BERT, and GPT2). We will apply this to real-world problems to create an NLP pipeline on top of the PyTorch framework and spaCy.
The course offers both theoretical and practical, lab-heavy modules. By completing you would be able to:
* Have working knowledge of PyTorch to train your own deep learning models.
* Use OpenVINO to run model optimizer
* Use less compute and memory for deploying model inference in production.
* Build end to end NLP pipeline with everything you learn
** Register and attend here:
(Free online tech event, you can join from anywhere. after register at this link, you will receive the join link. also receive recordings if you miss the live sessions. thanks)
This three hour Apache Kafka workshop will explore three advanced topics relating to the distributed event streaming platform. The breakdown for the workshop will be as follows:
For the first hour, the workshop will begin with comparison between Legacy Monolithic Architecture with Microservice Architecture. For Kafka Solutions, it will cover Event Driven Architecture and Kafka fundamental concepts including Partitions and Streams.
The second hour of the workshop will cover Kafka Producers, Consumers, Connectors, and Schema Registry. We will provide example code for a Producer, a sample Consumer, 3rd party connector, and examples of schema type Avro/Json/other formats.
For the last hour, we will discuss Kafka Cluster Deployment. This discussion will include deploying a broker, Zookeeper, Schema Registry, Producer and Consumer Config settings, enabling SSL, setting ACL for each topic, enabling firewall, and providing examples for each. We will also cover Kafka monitoring including Metricbeat or Prometheus with Alertmanager and JMX_Exporter.
More AI/ML/Data Tech events up coming (join from anywhere with zoom):
* May 12th, Project Nessie: A git-like experience for Data Lake
* May 12th, Ballista- Distributed Compute with Apache Arrow and Rust
* May 17th, The Bayesians are Coming to Time Series
* May 19th, Interactive SQL on the Lakehouse: Making BI work without Data Warehouses and Extracts
* May 20, NLP Advances for African Languages
* Jun 22~24, Ray Summit - Scalable ML and Python (free, virtual conference)
Details and registration: https://www.aicamp.ai/event/events
** 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.
* 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