Key Takeaways -   To understand data science, one needs a lot of technical expertise along with business understanding. Generative AI, MLOps, and clou ...

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...

In the previous three articles, I explained the mechanism of PCA from scratch. Because you have the experience of manual calculations with NumPy, you understand what the library is doing behind the ...

In the previous article, we learned the basic concept of PCA. Based on the idea of "finding the direction where the data is most spread out," we tried every angle from 0 to 180 degrees in 1-degree ...

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 ...

Part II: Unsupervised machine learning in R to cluster and identify candidate countries for international expansion, using PCA, K-Means, and DBSCAN.

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 ...

Various regulatory bodies have published ethical principles, codes, and/or guidelines for mental health practice globally. Although such guidelines may lend themselves equally relevant, there seems a ...

Electroencephalogram (EEG) analysis has shown significant research value for brain disease diagnosis, neuromodulation and brain-computer interface (BCI) application. The analysis and processing of EEG ...

ABSTRACT: This study applies Principal Component Analysis (PCA) to evaluate and understand academic performance among final-year Civil Engineering students at Mbeya University of Science and ...

Sparse principal component analysis (SPCA) extends classical principal component analysis to settings where the number of variables greatly exceeds the number of observations. By imposing sparsity ...