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Model optimization techniques
When I used to look at my model sizes once training gets over I always gets frustrated because of the number it shows up. But no more worries as the machine learning world has developed immensely…
Read more at Analytics Vidhya | Find similar documentsOptimizing Model Parameters
Optimizing Model Parameters Now that we have a model and data it’s time to train, validate and test our model by optimizing its parameters on our data. Training a model is an iterative process; in eac...
Read more at PyTorch Tutorials | Find similar documentsHow your model is optimized | Know your Optimization
The driver behind a lot of models that the average Data Scientist or ML-engineer uses daily relies on numerical optimization methods. Studying the optimization and performance of different functions…
Read more at Towards Data Science | Find similar documentsOptimization
Case Study: Optimization in Python Using Gekko Problem Scope Now let’s dive in to find out what would be the optimal solution in which we maximize product sales by manufacturing appropriate product u...
Read more at Analytics Vidhya | Find similar documentsSolving Optimization Problems in Machine Learning
Optimization, to put it in simple terms, is the process of minimizing the cost or the loss function through various algorithms. This is achieved by finding the minima of a loss function(or cost…
Read more at Analytics Vidhya | Find similar documentsModel Optimization with TensorFlow
Reduce your models' latency, storage, and inference costs with quantization and pruning Continue reading on Towards Data Science
Read more at Towards Data Science | Find similar documentsOptimization with Surrogate Models via Symbolic Regression
Performing an optimization is a very interesting task. In our daily life, we might be interested in the best way to get to work in the shortest amount of time, or maybe in the best particle size of ou...
Read more at Towards Data Science | Find similar documentsTaking Your Optimization Skills to the Next Level
Photo by Lukas Leitner on Unsplash Soft constraints, linearization, multi-objectives and more If you are an optimization beginner, I would recommend you to start with the why and the how, before retur...
Read more at Towards Data Science | Find similar documentsNeural Network Optimization
This article is the third in a series of articles aimed at demystifying neural networks and outlining how to design and implement them. In this article, I will discuss the following concepts related…
Read more at Towards Data Science | Find similar documentsA Gentle Introduction to Function Optimization
Last Updated on October 12, 2021 Function optimization is a foundational area of study and the techniques are used in almost every quantitative field. Importantly, function optimization is central to ...
Read more at Machine Learning Mastery | Find similar documentsOptimization (
Optimization ( scipy.optimize ) Contents Optimization ( scipy.optimize ) Unconstrained minimization of multivariate scalar functions ( minimize ) Nelder-Mead Simplex algorithm ( method='Nelder-Mead' )...
Read more at SciPy User Guide | Find similar documentsBayesian Optimization: A step by step approach
Optimizing a function is super important in many of the real life analytics use cases. By optimization we mean, either find an maximum or minimum of the target function with a certain set of…
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