Rubens A. Zimbres

Lecture at Google Sao Paulo - Brazil

Senior Data Scientist and Machine Learning Engineer


Dual Master and Doctor in Business Administration and Electrical Engineering


Certified Google Cloud Professional Data Engineer


Google Developer Expert in AI/Machine Learning (NLP) and Google Cloud Platform (Security)


CompTIA Security+ certified


AWS Certified Cloud Practitioner and AWS Certified Machine Learning - Specialty


Links

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Disclaimer: three elements of this website were developed with Generative AI ⚠

Contributor for the cybersecurity project OWASP Top 10 for Large Language Model Applications

My collection of pins from the Google Developers Experts program, Google Cloud Champions Innovators and NEXT '24. As many of them involve a certain level of difficulty, this makes them special for me.

LATEST UPDATES

👽 On April 9th I was on Google Cloud Next'24 in Las Vegas (Champions and Certified Lounge) presenting Langchain and Gemini deployed in a Google Cloud infrastructure (Dialogflow and Cloud Run) 👽

Google Cloud Champions Innovators at Next'24 Las Vegas

DevFest Experts Bootcamp in Sunnyvale - California

Google event in Colombia - NATION

GENERATIVE   AI   APP

This Generative AI application was developed with Python + Google Cloud Generative AI Studio, and deployed in a container (Cloud Run) running a Flask application.

You can ask the app details about my personal path, experience, projects delivered, education and languages.


You can use prompts like this:

Tell me about Rubens experience and the languages he speaks

Did Rubens work with predictive modeling ?

Does he have experience with application security?

  Enter prompt here

Tutorial on how to deploy this Gen AI app: here

PROJECTS DELIVERED

Some projects I delivered and their details

ACTIVITY

My Google Developers profile

Articles about Google Cloud infrastructure, Vertex AI, Recommenders, Agent-Based Modeling, Graph Neural Networks, Object Detection, Tensorflow and Cybersecurity

Articles about Google Cloud, Deep Learning, NLP, Agent-Based Modeling, Kubernetes, Transformers, Ethical Hacking, Pentesting, Social Networks

Python codes along my journey as Data Scientist. Machine Learning, Deep Learning, NLP, Transformers, Google Cloud, Algorithmic trading, Tensorflow, Keras and PyTorch

My profile at Google Experts Directory

My badges related to the courses and LABs I completed 

My previous experience, education, licenses, certifications, published papers and patents

My questions and answers in StackOverflow. I am a recognized member of the Google Cloud Collective

My certifications in Machine Learning, Deep Learning, Google Cloud and Ethical Hacking

Academic papers published during my Master and Doctorate

My three patents, two in NLP and one in Cellular Automata

I am a featured contributor at Wolfram Community, with 2 Staff Picks and 40,000 article views

FEATURED CONTENT

Tutorial about fine tuning Google’s open model Gemma-2b via HuggingFace and PyTorch to solve Mathematical problems

Here, I explore the phases, methodologies, and potential impacts of a Transfer Learning attack.

Tutorial about building a Knowledge Graph from scratch using Neo4j and Cypher

Article about deploying Gemini on Google Kubernetes Engine (GKE) and Dialogflow.

In this article, I use LangChain and GPT-4 to evaluate Google’s open model Gemma-2B-it in 22 criteria.

I made Google's open source model Gemma collaborate with OpenAI’s gpt-3.5 to generate a graph plot from a simple natural language sentence at a low cost. 

Here I create a Knowledge Graph storing scraped data in a structured manner, and using this data with LangChain to create a chatbot with memory

Article on how to use pgvector on a PostgreSQL database for RAG (Retrieval Augmented Generation) with LLMs.

A tutorial on how to identify the presence of Pegasus spyware on an iPhone

A Jupyter notebook about Two Towers Recommender in Tensorflow for Recruiting

Generative AI article on how to generate Python code using RAG + LangChain + LLM

Tutorial about installing an IDS for personal protection

OWASP Top 10 for LLMs, published at Google Developer Experts blog

Q&A Generative AI application in Google Cloud, published at Google Cloud blog

Generative AI automation to “read” and organize pedagogical projects in clusters

Setup of NVIDIA Merlin and Tensorflow for Recommendation Models, published in Google Developer Experts

Google Cloud Contact Center Artificial Intelligence (CCAI): A Managerial View

Two Towers Recommender: A Custom Pipeline in Vertex AI Using Kubeflow, published in Google Developer Experts

Search of Brazilian Laws using Dialogflow CX chatbot engine and Vertex AI Matching Engine

Graph Neural Networks: the message passing algorithm, published in Google Developer Experts

Develop Secure End-to-End Machine Learning Solutions in Google Cloud

My article on Attacking Active Directory in a Windows Server network with Kali Linux

Agent-Based Modeling with Python, NetLogo and Arduino

Burn a physical security key using a nRF52840 Dongle from Nordic to securely access your Google / Google Cloud accounts

In this article I will present the steps to create a Generative Adversarial Network. 

In this post, I explain how to run an IoT project from the command line, using Ubuntu Core in a Raspberry Pi 3. 

My first project with an IoT device and AWS IoT. It collects CPU Temperature in real time, send to Amazon AWS IoT and make it available for Machine Learning models and dashboards.

Based on people's contacts with each other, you can easily see the whole social network analysis.

My attempt to explain Schrodinger's Equation and CP Violation.

This is a code I developed with Wolfram Mathematica, while trying to solve an Atari game. An application in traffic is presented.

If you want to receive my articles on Medium, or provide feedback on this website. 💬

PRESENTATIONS

GANs_Summer_School_16_LAYOUT
Google Cloud Basics***
150_Machine_Learning_Formulas.pdf

RECOMMENDED CONTENT

People of AI is a podcast of Gus Martins and Ashley Oldacre from Google showcasing inspiring people with interesting stories in the world of Artificial Intelligence (AI) and its subset, Machine Learning (ML). 

The podcast will interview leaders, practitioners, researchers and learners in the field of AI/ML and invite them to share their stories, what they are building, lessons learned along the way, and excitement for the AI/ML industry.

For all the episodes, visit the People of AI page at: https://peopleofai.libsyn.com/

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