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A Practical Guide to Feature Scaling in Machine Learning

Introduction Feature scaling is one of the most overlooked yet crucial steps in the machine learning pipeline. It’s the quiet hero ensuring that your models converge faster, predictions stay accurate, and algorithms behave as expected. Whether you’re a beginner or a seasoned data scientist, understanding when and how to scale your features can make all…

Understanding Consistent Hashing: Improving Distributed Caching Efficiency

Introduction:In the realm of distributed systems and caching mechanisms, the concept of consistent hashing plays a vital role in optimizing efficiency and reliability. By understanding how consistent hashing works and its significance in distributed caching, we can delve deeper into improving the scalability and performance of our systems. 1. What is Hashing?Hashing is a fundamental…

Fintech

Regime selection Predicted regimes in S&P index price using Hidden Markov Gaussian mixture models. Market Basket Analysis Market Basket Analysis and Mining Association RulesProject: Proposed a model that analyzes customer behavior iteratingthrough different range of values for support and confidence• Used Apriori Principle and FP Tree for candidate pruning and rulegeneration• Formulated a model that…

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