PinnedLavanya Gupta·Feb 19, 2021Precision-Recall Tradeoff for Real-World Use CasesAce your ML interview by quickly understanding which real-world use cases demand higher precision, and which ones demand a higher recall…A response icon3A response icon3
PinnedLavanya Gupta·Nov 12, 2020Differences Between Word2Vec and BERTWith so many advances taking place in Natural Language Processing (NLP), it can sometimes become overwhelming to clearly understand the…A response icon3A response icon3
Lavanya Gupta·Apr 26, 2021Batch Normalization and ReLU for solving Vanishing GradientsA logical and sequential roadmap to understanding the advanced concepts in training deep neural networks.A response icon2A response icon2
Lavanya Gupta·Mar 2, 2021Interpreting Logistic Regression Coefficients the Right WayLearn to correctly interpret the coefficients of Logistic Regression and in the process naturally derive its cost function — the Log…
Lavanya Gupta·Mar 1, 2021Why Gradient Descent doesn’t converge with unscaled features?Ever felt curious about this well-known axiom? “Always scale your features” Well, read on to get a quick graphical and intuitive…A response icon1A response icon1
Lavanya Gupta·Jan 28, 2021Focal Loss — What, Why, and How?Focal Loss explained in simple words to understand what is it, why is it required and how is it useful — in both an intuitive and…A response icon2A response icon2
InWiCDSbyLavanya Gupta·Jan 1, 2021Basics of Image ProcessingEmpower your deep learning models by harnessing some immensely powerful image processing algorithms.
Lavanya Gupta·Nov 21, 2020Comparison of Hyperparameter Tuning algorithms: Grid search, Random search, Bayesian optimizationIn the model training phase, a model learns its parameters. But there are also some secret knobs, called hyperparameters, that the model…A response icon2A response icon2
