PCA
LDA/ Linear Discriminant Analysis is a very common technique used in supervised learning’s classification problems similar to PCA/ Principal Component Analysis which is used in Unsupervised Learning problems. LDA similar to PCA is a dimensionality reduction technique used as a pre-processing step in machine learning and pattern classification applications. Dimensionality reduction techniques can be used […]
Artificial Intelligence applications are taking over the world in almost all the possible areas known and to for artificial intelligence to be developed, machine learning lrequires lots and lots of training data, more the better. So large data sets are though useful but on the flip side, using a large data set has its own […]
The intense AI and ML projects and discussions continue week after week. We had almost 25+ folks attend the lab in Bangalore and 10+ in Gurgaon including two visitors from New York and Melbourne with many more on the hangout. Bangalore: Vivek started with a discussion of Principal Component Analysis. PCA is a dimensionality reduction […]