2019 ♦ Houston TensorFlow & Applied AI/ML user group (TensorFlow.org approved) … Valentino Moreign (founder & primary organizer)

2019 ♦ Houston Kotlin user group (KotlinLang.org/JetBrains approved) … Zane Moreign (founder & primary organizer)

2019 ♦ Houston PostgreSQL user group … Zane Moreign (founder & primary organizer)

2018 ♦ Houston Google Cloud user group (a.k.a. GDG Cloud Houston) … Google requested us to run it … Valentino Moreign (founder & primary organizer)

2017 ♦ HCCUG.org™ revamp … and exploded from a cozy <300 members to ~1K in 1 year … see about us

2010 ♦ Houston C & C++ user group… to focus on what {Tex} calls Crux Computing (covering Rust, D, etc.)

2008 ♦ Houston Cloud Computing user group… {HCCUG.org} to focus on Performance Computing (includes Cluster, IoT, and Quantum computing)

DISCLOSURE:

1. This is NOT an HCCUG.org™ event. HIA does NOT charge for FIRST TIME ATTENDEES.

2. PLEASE SEE Houston Investors Association for all details regarding this event

3. We appreciate HIA President Bob for inviting Zane to speak!

"Simple_Safety™ 2020-Q1 Edition" ~ by Zane Moreign

• This is next installment of Zane's Simple_Safety™ Series ... our first "Hangout-n-Learn" event is with our friends, the 20+ year old Houston Linux User Group (HLUG) Zane demoed the GCP (Google Cloud Platform) and the gotchas in Google's Qwiklabs training.

• Apache Spark, MapR, Scala … from the perspective of a veteran!!!

• where ⟹ cPanel, Inc. 2550 North Loop West, Houston, TX 77092

NOTE: IF DOOR IS LOCKED PLEASE CALL HLUG's Marco (# will be posted on the door)

DISCLOSURE:

1) This is NOT an HCCUG.org™ managed event or a combined special event — HCCUG.org™ is only presenting at HLUG — continuing our focus of community BRIDGING just like we have done over the decade (e.g., Houston Azure, HSPUG, HASSUG, HDNUG, and more, including those out-of-state :-)

2) This event is made possible because of the warm welcome from Ed (President of HLUG) and other HLUG folks!

3) As y'all know there is no-charge to attend HCCUG.org™ events. Likewise, HLUG too does not charge for their events.

4) Like us, they too have Pizza. Unlike us, they do NOT have PRE-registration, so you do not get to select your food ‒BUT‒ on the PLUS side you can just walk-in ... no registration required :-)

5) We will follow our hosts format, there will be a short talk by Zane Moreign ... this is the next installment in Zane's ongoing Simple_Safety™ Series ... and the rest of the time is to Hangout with our HLUG friends :-)

Hands-On with Swift for TensorFlow – A Next-Generation Deep Learning Framework ~ by Ethan Saadia

• where ⟹ HCCUG.org @ Tracy Gee Community Center, 3599 Westcenter Dr, Houston, TX 77042

• with FREE parking, data privacy, badger-free attendance, Food & Beverages, etc … ⟿ REGISTER HERE (confirmations sent on rolling basis)

Swift is a modern and expressive programming language developed and open-sourced by Apple. Although the language of choice for Apple platforms, Google has chosen Swift for its next-generation deep learning framework. Swift’s static type system and performance make it a great fit for machine learning, and Google has integrated many powerful tools into the platform. The talk will cover these major features, and then I will do a live image classification demo. Automatic Differentiation Computing the gradients of models and loss functions are essential for training machine learning models. Swift for TensorFlow includes automatic differentiation that enables you to differentiate functions and custom types without extra code. Python Interoperability Python has a myriad of prominent libraries for data science and numerical computing, including NumPy, Pandas, and Matplotlib. As a younger language, Swift does not yet have libraries to provide all this functionality, but Google has made Python fully interoperable with Swift. You can seamlessly import Python libraries, use Python objects in Swift, and vice versa. Image Classification Demo Swift for TensorFlow is fully usable without any installation on any device with an internet connection. The toolchain is preinstalled on special Google Colab notebooks, Jupyter notebooks hosted in the cloud that work like Google Docs. I will provide a link to a custom notebook so attendees can follow along with the demo on their own devices. The demo involves creating a dataset, designing a convolutional neural network, building a custom training loop, visualizing model performance during training, and running inferences. The notebook showcases Swift for TensorFlow and its key features, Python interoperability and automatic differentiation. Swift is designed to feel familiar, so the code is approachable to developers who may not be familiar with Swift or machine learning.

Here is the notebook link: https://colab.research.google.com/drive/1VbOH3sWYCe14CNnvvjAVkN0mQepv05Ng