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Google Developer Expert - Dharmesh Vaya - 2024 Contributions

Updated
3 min read
Google Developer Expert - Dharmesh Vaya - 2024 Contributions

Dharmesh is a Solutions Architect with a proven track record of developing robust enterprise applications on cloud platforms. He's passionate about fostering a culture of innovation within teams and currently works at Palo Alto Networks as a Cloud Security Architect.

Beyond his professional role, Dharmesh is a dedicated community leader. He used to actively manage the Google Cloud Developers Community in Mumbai, sharing his expertise and passion for cloud technologies.

A sought-after speaker at various conferences, Dharmesh also generously dedicates his time to mentoring students, young professionals, and local businesses, guiding them on leveraging the power of the Google Cloud Platform. His commitment to both technical excellence and community engagement makes him a valuable asset to the tech landscape.

Here are some of this notable contributions during 2024 -

Deploying Gemma AI Models on Google Kubernetes Engine with GPUs | Dharmesh Vaya | Kubetools Day 3.0

https://www.youtube.com/watch?v=Nd8Rli9CXxM

Deploying Gemma AI Models on Google Kubernetes Engine with GPUs | Dharmesh Vaya | Kubetools Day 3.0

Podcast - Ft. Dharmesh Vaya, Solutions Architect @paloaltonetworks | GDE In Google Cloud

https://www.youtube.com/watch?v=JepdsCyt-Fc

#ccdgn24 Podcast - Ft. Dharmesh Vaya, Solutions Architect @paloaltonetworks  | GDE In Google Cloud

Building practical applications with Gemini and LangChain4j

Building practical applications with Gemini and LangChain4j

Scaling Your AI Applications Effortlessly using Cloud Run

Scaling Your AI Applications Effortlessly using Cloud Run

Deploying Chatbot powered by Google Gemini

Deploying Chatbot powered by Google Gemini

Building practical applications with Gemini and LangChain4j

Talk Title: Building practical applications with Gemini and LangChain4j Abstract: This talk will explore the integration of Google AI's Gemini language model with Java, leveraging the LangChain4j framework. We'll delve into practical applications, from simple prompts to complex tasks like multimodal inputs, information extraction, and sentiment analysis. You'll learn how to set up a Java project, craft effective prompts, and stream responses efficiently. We'll also discuss advanced techniques like Retrieval Augmented Generation (RAG) and function calling to enhance your applications.

Building practical applications with Gemini and LangChain4j

AI for all - The Gemini Ecosystem

 AI for all - The Gemini Ecosystem

RAG Chatbot on GKE: A Hands-on Guide

RAG Chatbot on GKE: A Hands-on Guide

Deploying Gemma AI Models on Google Kubernetes Engine with GPUs

Deploying Gemma AI Models on Google Kubernetes Engine with GPUs

Revolutionizing Retail Search with Vertex AI and Elastic

Revolutionizing Retail Search with Vertex AI and Elastic

Scaling your AI applications effortlessly using Cloud Run

Scaling your AI applications effortlessly using Cloud Run

Securing your LLMs

Securing your LLMs

Building a Secured CI/CD on GCP (Kazakhstan)

Building a Secured CI/CD on GCP