October 16, 2025

Master Vision Transformers for Image Classification: Boost Performance Over CNN

By Alireza Pourmahdavi October 16, 2025

Introduction “Vision transformers have revolutionized the way we approach image classification, offering significant advantages over traditional convolutional neural networks (CNNs). Unlike CNNs, which focus on local features, vision transformers (ViTs) divide images into patches and use self-attention to capture global patterns, leading to higher accuracy and performance. In this article, we’ll explore how ViTs work, […]

Boost YOLOv8 Object Detection

By Alireza Pourmahdavi October 16, 2025

Introduction To get the most out of YOLOv8’s advanced object detection capabilities, configuring it to leverage GPU acceleration is essential. By tapping into GPU power, YOLOv8 can significantly speed up both training and inference, making it ideal for real-time object detection tasks. This guide will walk you through the necessary hardware, software, and driver setups, […]

Boost LLM Inference: Optimize Speculative Decoding, Batching, KV Cache

By Alireza Pourmahdavi October 16, 2025

Introduction Optimizing LLM inference is crucial for improving performance and reducing costs in modern AI applications. As Large Language Models (LLMs) become more prevalent, challenges like high computational costs, slow processing times, and environmental concerns must be addressed. Key techniques such as speculative decoding, batching, and efficient KV cache management are vital to boost speed, […]

Optimize LLM Inference: Boost Performance with Prefill, Decode, and Batching

By Alireza Pourmahdavi October 16, 2025

Introduction LLM inference optimization is essential for improving the performance of Large Language Models (LLMs) used in tasks like text generation. As LLMs become increasingly complex, optimizing phases like prefill and decode is key to enhancing speed, reducing costs, and managing resources more effectively. This article dives into strategies such as speculative decoding, batching, and […]

Master Multiple Linear Regression with Python, scikit-learn, and statsmodels

By Alireza Pourmahdavi October 16, 2025

Introduction Mastering Multiple Linear Regression (MLR) with Python, scikit-learn, and statsmodels is essential for building robust predictive models. In this tutorial, we’ll walk through how MLR can analyze the relationship between multiple independent variables and a single outcome, offering deeper insights compared to simple linear regression. By leveraging powerful Python libraries like scikit-learn and statsmodels, […]

Master Multiple Linear Regression in Python with scikit-learn and statsmodels

By Alireza Pourmahdavi October 16, 2025

Introduction Mastering multiple linear regression in Python with libraries like scikit-learn and statsmodels is an essential skill for any data scientist. In this article, we’ll walk you through the process of implementing and evaluating multiple linear regression models, using tools like scikit-learn and statsmodels to preprocess data, select features, and address challenges like multicollinearity and […]

Boost Object Detection with Data Augmentation: Master Rotation & Shearing

By Alireza Pourmahdavi October 16, 2025

Introduction To improve object detection accuracy, data augmentation techniques like rotation and shearing play a key role. These transformations help models recognize objects from multiple angles and perspectives, making them more robust in real-world scenarios. Rotation prevents overfitting by allowing the model to handle varying object orientations, while shearing simulates perspective distortions that are commonly […]

Boost Object Detection with Data Augmentation: Rotation & Shearing Techniques

By Alireza Pourmahdavi October 16, 2025

Introduction “Data augmentation is a powerful technique that boosts the performance of object detection models, especially through rotation and shearing. These transformations allow models to recognize objects from various angles, helping to reduce overfitting and making them more adaptable to real-world scenarios. In this article, we dive into how rotation and shearing work to improve […]

Master Ridge Regression: Reduce Overfitting in Machine Learning

By Alireza Pourmahdavi October 16, 2025

Introduction Ridge regression is a powerful technique in machine learning, designed to combat overfitting by applying an L2 penalty to the model’s coefficients. This helps to stabilize coefficient estimates, especially in cases with correlated features or multicollinearity. Unlike Lasso regression, Ridge doesn’t eliminate any features but instead shrinks their impact, leading to a more reliable […]

Fix Network Performance: Optimize MTU, iperf3, and mtr Tools

By Alireza Pourmahdavi October 16, 2025

Introduction To resolve network performance issues effectively, it’s essential to optimize tools like iperf3, mtr, and MTU settings. These powerful diagnostic tools help identify and fix network asymmetry, which can lead to slow speeds and unreliable connections. In this tutorial, we’ll walk through the process of using iperf3 and mtr to diagnose network issues caused […]

Alireza Pourmahdavi

I’m Alireza Pourmahdavi, a founder, CEO, and builder with a background that combines deep technical expertise with practical business leadership. I’ve launched and scaled companies like Caasify and AutoVM, focusing on cloud services, automation, and hosting infrastructure. I hold VMware certifications, including VCAP-DCV and VMware NSX. My work involves constructing multi-tenant cloud platforms on VMware, optimizing network virtualization through NSX, and integrating these systems into platforms using custom APIs and automation tools. I’m also skilled in Linux system administration, infrastructure security, and performance tuning. On the business side, I lead financial planning, strategy, budgeting, and team leadership while also driving marketing efforts, from positioning and go-to-market planning to customer acquisition and B2B growth.

Master Vision Transformers for Image Classification: Boost Performance Over CNN

Master Vision Transformers for Image Classification: Boost Performance Over CNN

Boost YOLOv8 Object Detection

Boost LLM Inference: Optimize Speculative Decoding, Batching, KV Cache

Optimize LLM Inference: Boost Performance with Prefill, Decode, and Batching

Master Multiple Linear Regression with Python, scikit-learn, and statsmodels

Master Multiple Linear Regression in Python with scikit-learn and statsmodels

Boost Object Detection with Data Augmentation: Master Rotation & Shearing

Boost Object Detection with Data Augmentation: Rotation & Shearing Techniques

Master Ridge Regression: Reduce Overfitting in Machine Learning

Fix Network Performance: Optimize MTU, iperf3, and mtr Tools

Alireza Pourmahdavi

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