Kernel Principal Component Analysis (PCA): Explained with an Example

Kernel Principal Component Analysis (PCA): Explained with an Example

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Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets such as two moons: PCA flattens the structure and mixes the classes together.  Kernel PCA fixes this limitation by mapping the data into a higher-dimensional feature space where nonlinear patterns become linearly separable. In this article, we’ll walk through how Kernel PCA works and use a simple example to visually compare PCA […]

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How to Build a Meta-Cognitive AI Agent That Dynamically Adjusts Its Own Reasoning Depth for Efficient Problem Solving

How to Build a Meta-Cognitive AI Agent That Dynamically Adjusts Its Own Reasoning Depth for Efficient Problem Solving

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In this tutorial, we build an advanced meta-cognitive control agent that learns how to regulate its own depth of thinking. We treat reasoning as a spectrum, ranging from fast heuristics to deep chain-of-thought to precise tool-like solving, and we train a neural meta-controller to decide which mode to use for each task. By optimizing the trade-off between accuracy, computation cost, and a limited reasoning budget, we explore how an agent can monitor its internal state and adapt its […]

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Healthcare Leaders, NVIDIA CEO Share AI Innovation Across the Industry

Healthcare Leaders, NVIDIA CEO Share AI Innovation Across the Industry

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AI is making inroads across the entire healthcare industry — from genomic research to drug discovery, clinical trial workflows and patient care. In a fireside chat Monday during the annual J.P. Morgan Healthcare Conference in San Francisco, NVIDIA founder and CEO Jensen Huang took the stage with industry leaders progressing each of these areas to advance biomedical science and meet the global demand for patient care. Healthcare has a more severe labor shortage than any other field — […]

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New machine-learning application to help researchers predict chemical properties

New machine-learning application to help researchers predict chemical properties

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One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule’s properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, they’re able to move forward with their work yielding discoveries that lead to medicines, materials, and more. Historically, however, the traditional methods of unveiling these predictions are associated with a significant cost — expending time and wear and tear on equipment, in addition to funds. Enter a […]

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