Adam vs SGD vs AdaGrad vs RMSprop vs AdamW – Day 39

Choosing the Best Optimizer for Your Deep Learning Model When training deep learning models, choosing the right optimization algorithm can significantly impact your model’s performance, convergence speed, and generalization ability. Below, we will explore some of the most popular optimization algorithms, their strengths, the reasons they were invented, and the types of problems they are best suited for. 1. Stochastic Gradient Descent (SGD) Why It Was Invented SGD is one of the earliest and most fundamental optimization algorithms used in machine learning and deep learning. It was invented to handle the challenge of minimizing cost functions efficiently, particularly when dealing...

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AdaGrad vs RMSProp vs Adam: Why Adam is the Most Popular? – Day 38

A Comprehensive Guide to Optimization Algorithms: AdaGrad, RMSProp, and Adam In the realm of machine learning, selecting the right optimization algorithm can significantly impact the performance and efficiency of your models. Among the various options available, AdaGrad, RMSProp, and Adam are some of the most widely used optimization algorithms. Each of these algorithms has its own strengths and weaknesses. In this article, we’ll explore why AdaGrad ( which we explained fully on day 37 ) might not always be the best choice and how RMSProp & Adam could address some of its shortcomings. AdaGrad: Why It’s Not Always the Best...

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