Multi-Agent Communication with the A2A Python SDK
If under a rock and you work with AI, you’ve probably heard about Agent2Agent (A2A) Protocol, “an open standard designed ...
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Bayesian Optimization for Hyperparameter Tuning of Deep Learning Models
to tune hyperparamters of deep learning models (Keras Sequential model), in comparison with a traditional approach — Grid Search. Bayesian Optimization Bayesian ...
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Why Regularization Isn’t Enough: A Better Way to Train Neural Networks with Two Objectives
neural networks, we often juggle two competing objectives. For example, maximizing predictive performance while also meeting a secondary goal like fairness, interpretability, ...
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Code Agents: The Future of Agentic AI
of AI agents. LLMs are no longer just tools. They’ve become active participants in our lives, boosting productivity and transforming ...
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How to Evaluate LLMs and Algorithms — The Right Way
Never miss a new edition of The Variable, our weekly newsletter featuring a top-notch selection of editors’ picks, deep dives, ...
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Do More with NumPy Array Type Hints: Annotate & Validate Shape & Dtype
array object can take many concrete forms. It might be a one-dimensional (1D) array of Booleans, or a three-dimensional (3D) ...
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New to LLMs? Start Here | Towards Data Science
to start studying LLMs with all this content over the internet, and new things are coming up each day. I’ve ...
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Prototyping Gradient Descent in Machine Learning
Learning Supervised learning is a category of machine learning that uses labeled datasets to train algorithms to predict outcomes and ...
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Estimating Product-Level Price Elasticities Using Hierarchical Bayesian
In this article, I will introduce you to hierarchical Bayesian (HB) modelling, a flexible approach to automatically combine the results ...
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Multiple Linear Regression Analysis | Towards Data Science
full code for this example at the bottom of this post. Multiple regression is used when your response variable Y ...
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