The subthalamic nucleus contains subpopulations with different contributions to deliberative decision-making based on noisy evidence and reward-driven preferences.

Abstract: Rise of predictive techniques have changed the manner we deal with disease diagnosis in healthcare domain. Earlier detail analysis of patient data records was done for disease prediction to ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...

Gradient boosted decision tree (GBDT) is a popular machine learning algorithm. Current open-sourced GBDT implementations are mainly designed for single output. When there are multiple outputs, they ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

If you want to learn the math behind data science and machine learning, 3Blue1Brown is the channel for you. Created by Grant Sanderson, 3Blue1Brown uses animation to explain complex mathematical ...