Optimization Algorithms

A Case for Constrained Regression — How often do you find that a major chunk of the business knowledge of your domain experts go in vain because your data science team cannot incorporate those into their AI models? …

Problem Statement: Dorian Auto manufactures luxury cars and trucks. The company believes that its most likely customers are high-income women and men. To reach these groups, Dorian Auto has embarked on an ambitious TV advertising campaign and has decided to purchase 1-minute commercial spots on two types of programs: comedy…

Overview Deep Learning is a subfield of machine learning which is used to perform complex tasks such as speech recognition, text classification, etc. A deep learning model consists of activation function, input, output, hidden layers, loss function, etc. Any deep learning model tries to generalize the data using an algorithm and…

An effective and easy-to-build/easy-to-use tool for global optimization. — Recently, we have published the first part of this post on the Differential Evolution (DE) optimization algorithm. In this second part, we give some details on its PyCUDA implementation. The code structure and the nomenclature reflect the formalism introduced in the previous post. The PyCUDA code will consist of CUDA…

It was 2008 and one of the latest of my undergrad + master’s degrees at the School of Engineering of Universidad de Chile. When done, I was planning to backpack around the world: travel so far east that I would reach home again. I had the time and energy, but…

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There are lots of definitions of AI. According to the Merrian-Webster dictionary, Artificial Intelligence is a large area of computer science that simulates intelligent behavior in computers. Based on this, an algorithm implementation based on metaheuristic called Particle Swarm Optimization (originaly proposed to simulate birds searching for food, the…

Optimization is the procedure where we train the model iteratively that outcomes in a max and lowest function appraisement. It’s one of the most major cautions in Machine Learning to pick up better outcomes. We equate the results in every iteration by modifying the hyperparameters in each shift until…

Save Hours With The Help of Transfer Learning & Optimizers — Deep learning is a subset of machine learning that utilizes neural networks in “deep” architectures, or multiple layers, to extract information from data. Early neural networks employed relatively simple (or “shallow”) architectures, but today’s deep learning neural networks can be incredibly complex. Neural networks are designed to work much like…