TJ GokkenProtjgokken.com·Oct 23, 2024From Theory to Reality: Understanding Machine Learning with ML.NETMachine learning uses algorithms to learn. Great, but how? How does it use these algorithms and which algorithm does what? Let’s break down some of the core concepts that power these intelligent algorithms, starting with one of the most important: Gr...DiscussAn Introduction to Data Training: Laying the Foundation for Machine LearningMachine Learning
Bitingo Josaphatbitingo-the-deep-neural-nets.hashnode.dev·Jun 8, 2024Beat Overfitting: Essential Regularization Techniques for Machine LearningIn machine learning, overfitting is a common problem where models perform well on training data but fail to generalize to unseen data. This article explores essential regularization techniques that help combat overfitting and improve model performanc...Aruna Christian and 2 others are discussing this3 people are discussing thisDiscuss·12 likes·155 readsregularization
Juan Carlos Olamendyjuancolamendy.hashnode.dev·Apr 23, 2024A Comprehensive Guide to Regularization in Machine LearningHave you ever trained a machine learning model that performed exceptionally on your training data but failed miserably on real-world, unseen data? If so, you've encountered overfitting, a common pitfall in machine learning that regularization techniq...DiscussMachine Learning
K Ahameddatailm.hashnode.dev·Jan 21, 2024Train Right, Predict Bright: Regularization Tricks for Futureproof ModelsIn the world of machine learning, the quest for the perfect model is a constant pursuit. We train complex algorithms on mountains of data, hoping they'll learn intricate patterns and make accurate predictions. But sometimes, our eagerness can backfir...DiscussMachine LearningMachine Learning
Akhil Soniakhilworld.hashnode.dev·Sep 1, 2023Early StoppingIn my blog (Regularization of ML models), I have already discussed different methods of regularization for a linear model. The regularization of a model means setting the parameters of the model in such a way that the cost function which is the perfo...Discuss·10 likesMachine Learning
Kavita Ranakavirana.hashnode.dev·Jun 25, 2023Lasso Regression or L1 RegularizationWhat does L1 mean? In Lasso Regression, we add a penalty term to the loss function during model training. The penalty term is proportional to the sum of the absolute values of the coefficients. We calculate the penalty term using the L1 norm, which i...Discuss·3 likesMachine Learning
Dharshini Sankar Rajdharshinisankarraj.hashnode.dev·Jun 10, 2023Regularization TechniquesOverfitting is a common challenge in deep learning, where a neural network becomes excessively specialized in the training data and fails to generalize well to unseen data. To combat overfitting, various regularization techniques have been developed....Discuss·1 like·206 readsneural networks
Yusuf Olaniyithe-data-trailblazer.hashnode.dev·Jun 6, 2023Improving the Performance of Machine Learning Models - Part 1Introduction istockphoto.com "The artist who aims at perfection in everything achieves it in nothing" - Eugene Delcroix In pursuit of perfection, the French artist - Eugene Delcroix once said "The artist who aims at perfection in everything achiev...Discuss·13 likes·144 readsregularization
Andrea D’Agostinodag.hashnode.dev·Apr 4, 2023L1 vs L2 Regularization in Machine Learning: Differences, Advantages and How to Apply Them in PythonMachine Learning is a discipline that is experiencing enormous development in the technological and industrial fields. Thanks to its algorithms and modeling techniques, it is possible to build models capable of learning from past data, generalizing a...DiscussMachine LearningMachine Learning
Jay Galagalacodes.hashnode.dev·Jan 8, 2023Regularization techniques for reducing varianceRegularization is a technique used in machine learning to prevent overfitting and reduce variance in a model. Overfitting occurs when a model is excessively complex and has learned even the noise in the training data, which can negatively impact the ...Discuss·2 likesregularization
