Welcome to the official Automatic Machine Learning group in Austin, Texas. Data Science can be done by everyone. Interactive Data Science is a thing now for Citizen Data Scientists, Business Leaders, and Domain Experts. The democratization of Data Science has arrived. With commodity family of software collectively called Automatic Machine Learning (AutoML), it's now possible for everyone to be able to contribute in this amazing field.
I created this group to understand more about the AutoML space within Data Science. Join me on this journey. This group is not only just about building data models fast... It's about learning Data Science fast too. This group is about rapid Data Science. Rapid comprehension comes when using using these tools. For the occasional programming topic, it will be lightweight discussions to speed this up using Pre-Templated Workflows and guided programming templates using tools such as d6flow and d6pipe.
This group is for everyone and has something for everyone. Model Building can take some time. Turn two weeks into two hours. This is possible today with the democratization of Data Science and AutoML accelerants: AIBLE, AutoKeras, AutoSKLearn, Auto-WEKA, Bell Integrator, BigSquid, Compellon, d6flow, d6pipe, DALEK, Data Robot, DeterminedAI, DotData, DMway, EdgeVerve, Gemini Data, Google Cloud AutoML, H2O, KNIME, Kraken, LIME, Ludwig, Microsoft AutoML, mljar, NumberTheory, Ople, Parsnip, RapidMiner, Splunk Data Science Toolkit, Squark, TPOT, TAZI, TransmogrifAI, XpanseAI
If you 😍 Lightning Fast Data Science, this is for you!
From AutoML.org site:
provides methods and processes to make Machine Learning available for non-Machine Learning experts, to improve efficiency of Machine Learning and to accelerate research on Machine Learning. Machine learning (ML) has achieved considerable successes in recent years and an ever-growing number of disciplines rely on it. However, this success crucially relies on human machine learning experts to perform manual tasks. As the complexity of these tasks is often beyond non-ML-experts, the rapid growth of machine learning applications has created a demand for off-the-shelf machine learning methods that can be used easily and without expert knowledge. We call the resulting research area that targets progressive automation of machine learning AutoML.
"Data scientists won't be replaced by AutoML, but those who use AutoML will replace those who don't."
Bumped this meetup by a day. This time we'll be discussing the recently published AutoML article written by Paul Balas. Make sure to read it here:
https://www.linkedin.com/pulse/automl-data-scientists-spend-more-time-learning-business-paul-balas/ Austin AutoML meetings are once a month and is for everyone at all skill levels.