Category: AI Stack
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5 GPU & vGPU Mistakes That Break VMware Private AI Foundation (and How to Fix Them)
Most failed VMware Private AI Foundation deployments break on host-side GPU configuration, not the model. Here are five vGPU mistakes in VCF 9.1 and the exact commands to confirm and fix each one.
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Introducing the AI Infrastructure Sizing & Cost Calculator
Over the past few months, I have been spending a lot of time exploring on AI infrastructure around VMware Private AI, NVIDIA AI Enterprise, RAG,
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ML Concepts – Evaluation Matrix and Equations
There are several classifiers can be used to identify the model’s effectiveness. You can assess using the evaluation metrics such as Accuracy, Recall, F1 Score,
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ML Concepts – Loss Function in ANN
The Loss Function is one of the important components of Neural Networks. Loss is nothing but a prediction error of Neural Net. And the method
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ML Concepts – Optimization Algorithm for Training Neural Network Model
Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning rate in order to reduce the
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ML Concepts – Linear Regression vs Logistic Regression
Classification Regression Analysis Linear vs Logistic Regression More about Logistic Regression Steps in Preparing Model using Logistic Regression
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ML Concepts – Understanding the Dataset
What is Dataset? Usually dataset refers to the data that you have, it is combined of both dependent as well as independent variables. In ML
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ML Concepts – Classification vs Regression
Classification Regression – Classification is the task of predicting a discrete class label.– In a classification problem data is labelled into one of two or
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ML Concepts – Encoding Categorical Data
There are two types of encoding the Categorical Data: One Hot Encoding Label Encoding or Target Encoding Example: One Hot Encoding – 100, 101, 010
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ML Concepts – ROC vs AUC
ROC (Receiver Operating Characteristic) AUC (Area Under Curve) – ROC Curve represents relationship between Recall and Specificity. – It is a performance measurement for the
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ML Concepts – What is Feature Scaling?
Feature Scaling Feature scaling is technique that will get mean and standard deviation of your feature in order to scale your feature. If we apply
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ML Concepts – Feature Selection – Filter Method vs Wrapper Method
Feature selection is a critical step that affects the ML model performance directly. Reducing the number of features has two main benefits in developing machine
Architect’s Toolkit
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- AI Infra Sizing & Cost Calculator
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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