{"componentChunkName":"component---src-templates-tags-tsx","path":"/tags/machine-learning-math/","result":{"data":{"allTagYaml":{"edges":[{"node":{"id":"speeches","description":"Some of the greatest words ever spoken.","image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#282818","images":{"fallback":{"src":"/static/4dd7b5f567d2699202bc626bbcda5936/7f071/speeches-cover.jpg","srcSet":"/static/4dd7b5f567d2699202bc626bbcda5936/7a1a9/speeches-cover.jpg 750w,\n/static/4dd7b5f567d2699202bc626bbcda5936/25ec5/speeches-cover.jpg 1080w,\n/static/4dd7b5f567d2699202bc626bbcda5936/28e43/speeches-cover.jpg 1366w,\n/static/4dd7b5f567d2699202bc626bbcda5936/7f071/speeches-cover.jpg 1400w","sizes":"100vw"},"sources":[{"srcSet":"/static/4dd7b5f567d2699202bc626bbcda5936/662b3/speeches-cover.webp 750w,\n/static/4dd7b5f567d2699202bc626bbcda5936/6e6c6/speeches-cover.webp 1080w,\n/static/4dd7b5f567d2699202bc626bbcda5936/e4be3/speeches-cover.webp 1366w,\n/static/4dd7b5f567d2699202bc626bbcda5936/04d29/speeches-cover.webp 1400w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.4407142857142857}}}}},{"node":{"id":"Tests","description":"Some very great tests even with a description wow! uhhhhhh","image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#484848","images":{"fallback":{"src":"/static/8bafcea43f0bc141b01ef5b43dd2003b/997dc/testimg1.jpg","srcSet":"/static/8bafcea43f0bc141b01ef5b43dd2003b/1a909/testimg1.jpg 750w,\n/static/8bafcea43f0bc141b01ef5b43dd2003b/997dc/testimg1.jpg 1080w","sizes":"100vw"},"sources":[{"srcSet":"/static/8bafcea43f0bc141b01ef5b43dd2003b/207cf/testimg1.webp 750w,\n/static/8bafcea43f0bc141b01ef5b43dd2003b/3c432/testimg1.webp 1080w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.663888888888889}}}}}]},"allMdx":{"totalCount":3,"edges":[{"node":{"excerpt":"Gradient descent is one of the most popular algorithms to train machine learning models. However, many of the popular machine learning models like lasso regression or support vector machines contain loss functions that are not differentiable. Because of this, regular gradient descent can not be used. One of the most commonly utilized techniques to circumvent this issue is to use subgradients instead of regular gradients. And in this article, you will learn how it's done.","frontmatter":{"title":"Subgradient Descent Explained, Step by Step","excerpt":"Gradient descent is one of the most popular algorithms to train machine learning models. However, many of the popular machine learning models like lasso regression or support vector machines contain loss functions that are not differentiable. Because of this, regular gradient descent can not be used. One of the most commonly utilized techniques to circumvent this issue is to use subgradients instead of regular gradients. And in this article, you will learn how it's done.","tags":["Machine Learning Math"],"date":"2021-07-27T19:49:21.503Z","timeToRead":18,"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#181818","images":{"fallback":{"src":"/static/8d667dbc302a08dd3745c90bfb78dfd9/87706/SubGradientDescent_Thumbnail2.png","srcSet":"/static/8d667dbc302a08dd3745c90bfb78dfd9/0dee1/SubGradientDescent_Thumbnail2.png 750w,\n/static/8d667dbc302a08dd3745c90bfb78dfd9/8beaa/SubGradientDescent_Thumbnail2.png 1080w,\n/static/8d667dbc302a08dd3745c90bfb78dfd9/87706/SubGradientDescent_Thumbnail2.png 1280w","sizes":"100vw"},"sources":[{"srcSet":"/static/8d667dbc302a08dd3745c90bfb78dfd9/a66aa/SubGradientDescent_Thumbnail2.webp 750w,\n/static/8d667dbc302a08dd3745c90bfb78dfd9/65dd5/SubGradientDescent_Thumbnail2.webp 1080w,\n/static/8d667dbc302a08dd3745c90bfb78dfd9/71d4d/SubGradientDescent_Thumbnail2.webp 1280w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.5625}}},"author":[{"id":"Boris Giba","bio":"Hi! I'm Boris and I run this website. You can find more information in the \"About\"-tab.","avatar":{"children":[{"fluid":{"base64":"data:image/jpeg;base64,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","aspectRatio":1,"src":"/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg","srcSet":"/static/ba9e631272af1b925d6491b30df3b36f/b3d27/boris.jpg 40w,\n/static/ba9e631272af1b925d6491b30df3b36f/5a735/boris.jpg 80w,\n/static/ba9e631272af1b925d6491b30df3b36f/6e81a/boris.jpg 120w,\n/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg 800w,\n/static/ba9e631272af1b925d6491b30df3b36f/97bce/boris.jpg 1878w","sizes":"(max-width: 800px) 100vw, 800px"}}]}}]},"fields":{"layout":"post","slug":"/machine_learning_math/subgradient_descent/"}}},{"node":{"excerpt":"Gradient descent is one of the most famous techniques in machine learning and used for training all sorts of neural networks. But gradient descent can not only be used to train neural networks, but many more machine learning models. In particular, gradient descent can be used to train a linear regression model! If you are curious as to how this is possible, or if you want to approach gradient descent with smaller steps and not jump straight to neural networks, this post is for you. You will learn how gradient descent works from an intuitive, visual, and mathematical standpoint and we will apply it to an exemplary dataset in Python.","frontmatter":{"title":"Gradient Descent for Linear Regression Explained, Step by Step","excerpt":"Gradient descent is one of the most famous techniques in machine learning and used for training all sorts of neural networks. But gradient descent can not only be used to train neural networks, but many more machine learning models. In particular, gradient descent can be used to train a linear regression model! If you are curious as to how this is possible, or if you want to approach gradient descent with smaller steps and not jump straight to neural networks, this post is for you. You will learn how gradient descent works from an intuitive, visual, and mathematical standpoint and we will apply it to an exemplary dataset in Python.","tags":["Machine Learning Math"],"date":"2021-04-03T19:07:33.321Z","timeToRead":23,"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#384858","images":{"fallback":{"src":"/static/97717e791c8dcde652d468d6f7784a65/87706/GradientDescentLinearRegression_Thumbnail.png","srcSet":"/static/97717e791c8dcde652d468d6f7784a65/0dee1/GradientDescentLinearRegression_Thumbnail.png 750w,\n/static/97717e791c8dcde652d468d6f7784a65/8beaa/GradientDescentLinearRegression_Thumbnail.png 1080w,\n/static/97717e791c8dcde652d468d6f7784a65/87706/GradientDescentLinearRegression_Thumbnail.png 1280w","sizes":"100vw"},"sources":[{"srcSet":"/static/97717e791c8dcde652d468d6f7784a65/a66aa/GradientDescentLinearRegression_Thumbnail.webp 750w,\n/static/97717e791c8dcde652d468d6f7784a65/65dd5/GradientDescentLinearRegression_Thumbnail.webp 1080w,\n/static/97717e791c8dcde652d468d6f7784a65/71d4d/GradientDescentLinearRegression_Thumbnail.webp 1280w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.5625}}},"author":[{"id":"Boris Giba","bio":"Hi! I'm Boris and I run this website. You can find more information in the \"About\"-tab.","avatar":{"children":[{"fluid":{"base64":"data:image/jpeg;base64,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","aspectRatio":1,"src":"/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg","srcSet":"/static/ba9e631272af1b925d6491b30df3b36f/b3d27/boris.jpg 40w,\n/static/ba9e631272af1b925d6491b30df3b36f/5a735/boris.jpg 80w,\n/static/ba9e631272af1b925d6491b30df3b36f/6e81a/boris.jpg 120w,\n/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg 800w,\n/static/ba9e631272af1b925d6491b30df3b36f/97bce/boris.jpg 1878w","sizes":"(max-width: 800px) 100vw, 800px"}}]}}]},"fields":{"layout":"post","slug":"/machine_learning_math/gradient_descent_for_linear_regression/"}}},{"node":{"excerpt":"Vectorization is one of the most useful techniques to make your machine learning code more efficient. In this post, you will learn everything you need to know to start using vectorization efficiently in your machine learning projects.","frontmatter":{"title":"Vectorization Explained, Step by Step","excerpt":"Vectorization is one of the most useful techniques to make your machine learning code more efficient. In this post, you will learn everything you need to know to start using vectorization efficiently in your machine learning projects.","tags":["Machine Learning Math"],"date":"2021-03-06T18:32:05.647Z","timeToRead":7,"image":{"childImageSharp":{"gatsbyImageData":{"layout":"fullWidth","backgroundColor":"#385868","images":{"fallback":{"src":"/static/48d3891f0b15a736311ac3dd1dd6eea6/87706/Vectorization_Thumbnail.png","srcSet":"/static/48d3891f0b15a736311ac3dd1dd6eea6/0dee1/Vectorization_Thumbnail.png 750w,\n/static/48d3891f0b15a736311ac3dd1dd6eea6/8beaa/Vectorization_Thumbnail.png 1080w,\n/static/48d3891f0b15a736311ac3dd1dd6eea6/87706/Vectorization_Thumbnail.png 1280w","sizes":"100vw"},"sources":[{"srcSet":"/static/48d3891f0b15a736311ac3dd1dd6eea6/a66aa/Vectorization_Thumbnail.webp 750w,\n/static/48d3891f0b15a736311ac3dd1dd6eea6/65dd5/Vectorization_Thumbnail.webp 1080w,\n/static/48d3891f0b15a736311ac3dd1dd6eea6/71d4d/Vectorization_Thumbnail.webp 1280w","type":"image/webp","sizes":"100vw"}]},"width":1,"height":0.5625}}},"author":[{"id":"Boris Giba","bio":"Hi! I'm Boris and I run this website. You can find more information in the \"About\"-tab.","avatar":{"children":[{"fluid":{"base64":"data:image/jpeg;base64,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","aspectRatio":1,"src":"/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg","srcSet":"/static/ba9e631272af1b925d6491b30df3b36f/b3d27/boris.jpg 40w,\n/static/ba9e631272af1b925d6491b30df3b36f/5a735/boris.jpg 80w,\n/static/ba9e631272af1b925d6491b30df3b36f/6e81a/boris.jpg 120w,\n/static/ba9e631272af1b925d6491b30df3b36f/2f1b1/boris.jpg 800w,\n/static/ba9e631272af1b925d6491b30df3b36f/97bce/boris.jpg 1878w","sizes":"(max-width: 800px) 100vw, 800px"}}]}}]},"fields":{"layout":"post","slug":"/machine_learning_math/vectorization/"}}}]}},"pageContext":{"tag":"Machine Learning Math"}},"staticQueryHashes":["13077718","1316742457","2907728042","3762220167"]}