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Seenivasa Ramadurai

Sreeni Ramadurai is a Cloud and AI Solution Architect with over 20 years of experience, specializing in Cloud (Azure ,AWS, GCP) , Microservices , gRPC,Deep Learning, GenAI, NLP, and Vector Databases.

Location Dallas. Texas Joined Joined on 
Denoising Images with Autoencoders: A Practical Guide Using MNIST Dataset- Part 2

Denoising Images with Autoencoders: A Practical Guide Using MNIST Dataset- Part 2

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4 min read

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Exploring Autoencoders:Anomaly Detection with TensorFlow and Keras Using the MNIST Dataset-Part-1

Exploring Autoencoders:Anomaly Detection with TensorFlow and Keras Using the MNIST Dataset-Part-1

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8 min read
Early Stopping in Machine Learning and Life: Knowing When Enough is Enough

Early Stopping in Machine Learning and Life: Knowing When Enough is Enough

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5 min read
Navigating Bias and Variance: Lessons from Learning to Ride a Bike

Navigating Bias and Variance: Lessons from Learning to Ride a Bike

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2 min read
Understanding Agile Roles Through AI: Comparing Encoder-Decoder, Encoder, and Decoder-Only Models to SM, PO, and BA

Understanding Agile Roles Through AI: Comparing Encoder-Decoder, Encoder, and Decoder-Only Models to SM, PO, and BA

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4 min read
PCA vs. t-SNE: Unveiling the Best Dimensionality Reduction Technique for Your Data

PCA vs. t-SNE: Unveiling the Best Dimensionality Reduction Technique for Your Data

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6 min read
We Are in the Penultimate Stage Before We See the Final Generative Model: Introducing OpenAI o1-preview

We Are in the Penultimate Stage Before We See the Final Generative Model: Introducing OpenAI o1-preview

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4 min read
How Outliers Affect the Mean: An Analogy with Leadership in a Company

How Outliers Affect the Mean: An Analogy with Leadership in a Company

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3 min read
Optimizing GenAI & AI Deployment: Harnessing Microsoft AI Services for Efficient and Scalable Solutions

Optimizing GenAI & AI Deployment: Harnessing Microsoft AI Services for Efficient and Scalable Solutions

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1 min read
AWS -IAM Policies Overview

AWS -IAM Policies Overview

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2 min read
Advanced Techniques in RAG: A Deep Dive into MMR, Self-Querying Retrievers, Contextual Compression, and Ensemble Retrieval

Advanced Techniques in RAG: A Deep Dive into MMR, Self-Querying Retrievers, Contextual Compression, and Ensemble Retrieval

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4 min read
Exploring Text Similarity with OpenAIEmbeddings and Dot Products in Python

Exploring Text Similarity with OpenAIEmbeddings and Dot Products in Python

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2 min read
DDoS Attack

DDoS Attack

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1 min read
Building a Digital Sanctuary: An AWS-Inspired Journey Through Cloud Architecture and Spiritual Connections

Building a Digital Sanctuary: An AWS-Inspired Journey Through Cloud Architecture and Spiritual Connections

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2 min read
"Omnipresence Explained: How God and Anycast IP Address Share a Common Principle"

"Omnipresence Explained: How God and Anycast IP Address Share a Common Principle"

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1 min read
Fallacies of Distributed computing Vs Human life

Fallacies of Distributed computing Vs Human life

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1 min read
Various types of neural networks and their key characteristics:

Various types of neural networks and their key characteristics:

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3 min read
Smart Endpoints and Dumb Pipes

Smart Endpoints and Dumb Pipes

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2 min read
Capacity Planning AKS Azure Kubernetes Service Cluster

Capacity Planning AKS Azure Kubernetes Service Cluster

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3 min read
Microservices Architecture Using Azure Container APPS & DAPR & KEDA

Microservices Architecture Using Azure Container APPS & DAPR & KEDA

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3 min read
Why should we use Protobuf in Web API as data transfer protocol.

Why should we use Protobuf in Web API as data transfer protocol.

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3 min read
Service Mesh -Microservices

Service Mesh -Microservices

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3 min read
DAPR Distributed Application Runtime

DAPR Distributed Application Runtime

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4 min read
MongoDB Data Model & Microservice Architecture

MongoDB Data Model & Microservice Architecture

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2 min read
Activation Functions, RNN, LLM, LangChain

Activation Functions, RNN, LLM, LangChain

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1 min read
Choosing between Retrieval-Augmented Generation (RAG) and Model fine-tuning

Choosing between Retrieval-Augmented Generation (RAG) and Model fine-tuning

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2 min read
Divine Transformations: An Analogy for LLM Quantization in Resource-Constrained Environments

Divine Transformations: An Analogy for LLM Quantization in Resource-Constrained Environments

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1 min read
Pre-training, Fine-tuning, and Transfer learning. To make these ideas more relatable, let's use a real-world analogy

Pre-training, Fine-tuning, and Transfer learning. To make these ideas more relatable, let's use a real-world analogy

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1 min read
Discover the Future of AI with My New Book: Developing GenAI Applications with LangChain, Semantic Kernel and Powered by LLMs

Discover the Future of AI with My New Book: Developing GenAI Applications with LangChain, Semantic Kernel and Powered by LLMs

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2 min read
Why Upskilling is Crucial for GenAI Adoption Across the Organization

Why Upskilling is Crucial for GenAI Adoption Across the Organization

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5 min read
Essential Skills to Become a Generative AI Developer

Essential Skills to Become a Generative AI Developer

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3 min read
Easy way to deploy FastAPI In Azure

Easy way to deploy FastAPI In Azure

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2 min read
Tech Jokes - GenAI

Tech Jokes - GenAI

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1 min read
Exploring the Spiritual Dimensions of LLM Architecture

Exploring the Spiritual Dimensions of LLM Architecture

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3 min read
About Me

About Me

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1 min read
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