Dimensionality Reduction
06
Dec
Principal Component Analysis (PCA) in Artificial Intelligence
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 […]
08
Apr
CellStrat AI Lab – Minutes From 6th. Apr, 2019 Bangalore & Gurgaon Meetups
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 […]
28
Aug
01
Nov
Types of Autoencoders
Tags:
AI,
artificial intelligence,
autoencoder,
autoencoders,
contractive autoencoders,
deep learning,
denoising autoencoders,
dimensionality,
Dimensionality Reduction,
machine learning,
ML,
overcomplete autoencoders,
reconstruction error,
reconstruction penalty,
regularization,
regularizer,
sparse autoencoders,
The curse of dimensionality,
types of autoencoders,
undercomplete autoencoders,