BigDataFr recommends: Introduction to Gradient Descent Algorithm (along with variants) in Machine Learning

Introduction

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Optimization is always the ultimate goal whether you are dealing with a real life problem or building a software product. I, as a computer science student, always fiddled with optimizing my code to the extent that I could brag about its fast execution.

Optimization basically means getting the optimal output for your problem. If you read the recent article on optimization, you would be acquainted with how optimization plays an important role in our real-life.

Optimization in machine learning has a slight difference. Generally, while optimizing, we know exactly how our data looks like and what areas we want to improve. But in machine learning we have no clue how our “new data” looks like, let alone try to optimize on it.

So in machine learning, we perform optimization on the training data and check its performance on a new validation data. […]

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By Faizan Shaikh
Source: analyticsvidhya.com