Not all MMM tools are equal: Meridian, Robyn, Orbit, and Prophet explained

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
Oak Ridge National Lab

DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
GitHub

mohansree14/Bayesian-Deep-Learning-for-Probabilistic-Financial-Forecasting

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
marktechpost

Meet Trackio: The Free, Local-First, Open-Source Experiment Tracker Python Library that Simplifies and Enhances Machine Learning Workflows

Experiment tracking is an essential part of modern machine learning workflows. Whether you’re tweaking hyperparameters, monitoring training metrics, or collaborating with colleagues, it’s crucial to ...
Frontiers

Interpretable machine learning approach for TBM tunnel crown convergence prediction with Bayesian optimization

Accurate prediction of crown convergence in Tunnel Boring Machine (TBM) tunnels is critical for ensuring construction safety, optimizing support design, and improving construction efficiency. This ...
Scientific Research Publishing

Snoek, J., Larochelle, H. and Adams, R.P. (2012) Practical Bayesian Optimization of Machine Learning Algorithms. arXiv: 1206.2944.

ABSTRACT: The rapid proliferation of the Internet of Things (IoT) and Industrial IoT (IIoT) has revolutionized industries through enhanced connectivity and automation. However, this expansion has ...
Wired

This AI Model Never Stops Learning

Modern large language models (LLMs) might write beautiful sonnets and elegant code, but they lack even a rudimentary ability to learn from experience. Researchers at Massachusetts Institute of ...
techannouncer

Unlocking Machine Learning Potential with Google Colab Python

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...