--- title: Training the Same Neural Network with Different Optimizers description: An exploration of how different optimization algorithms (like SGD, Adam, RMSprop) affect neural network training when using the same model architecture and... canonical: https://daily.dev/posts/training-the-same-neural-network-with-different-optimizers-xiub2zc4q twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Training the Same Neural Network with Different Optimizers | daily.dev og:description: An exploration of how different optimization algorithms (like SGD, Adam, RMSprop) affect neural network training when using the same model architecture and... og:url: https://daily.dev/posts/training-the-same-neural-network-with-different-optimizers-xiub2zc4q og:image: https://api.daily.dev/og/posts/xIuB2Zc4q.png og:image:alt: Training the Same Neural Network with Different Optimizers og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Training the Same Neural Network with Different Optimizers **[Pranav Bh](https://daily.dev/sources/8exkfh5h0zpqdxgfg5ph2)** · [@bhpranav](https://daily.dev/bhpranav) · 1 min read · 0 upvotes · 0 comments ## Summary An exploration of how different optimization algorithms (like SGD, Adam, RMSprop) affect neural network training when using the same model architecture and dataset. The piece examines what changes in training dynamics, convergence behavior, and final performance when only the optimizer varies. ## Content Same Model, Same Data, Varying Optimizers: What Actually Changes? [https://pub.towardsai.net/training-the-same-neural-network-with-different-optimizers-498c4a37748c](https://pub.towardsai.net/training-the-same-neural-network-with-different-optimizers-498c4a37748c) ## Similar posts on daily.dev - [Optimization: Gradient Descent to Adam](https://daily.dev/posts/optimization-gradient-descent-to-adam-ymvhymxv0) · Medium · 0 upvotes · 0 comments - [The Machine Learning “Advent Calendar” Bonus 2: Gradient Descent Variants in Excel](https://daily.dev/posts/the-machine-learning-advent-calendar-bonus-2-gradient-descent-variants-in-excel-c2hl8etlj) · Towards Data Science · 1 upvotes · 0 comments - [16 Techniques to Optimize Neural Network Training](https://daily.dev/posts/16-techniques-to-optimize-neural-network-training-3pfjapxq9) · Daily Dose of Data Science \| Avi Chawla \| Substack · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks) [View this post on daily.dev](https://daily.dev/posts/training-the-same-neural-network-with-different-optimizers-xiub2zc4q) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"DiscussionForumPosting","mainEntityOfPage":"https://daily.dev/posts/training-the-same-neural-network-with-different-optimizers-xiub2zc4q","headline":"Training the Same Neural Network with Different Optimizers","text":"An exploration of how different optimization algorithms (like SGD, Adam, RMSprop) affect neural network training when using the same model architecture and dataset. 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