Krishna PullakandamTomek Links: Undersampling Technique for Fraud DetectionIn fraud detection problems, one of the biggest challenges Data Scientists / ML Engineers face is dealing with imbalanced datasets. Since…Sep 41Sep 41
Krishna PullakandamDetecting Label Errors and Boosting Model Performance with CleanlabThere is a general rule in the world of Machine Learning that the quality of your data can make or break your model. One often overlooked…Aug 23Aug 23
Krishna PullakandamHyper-parameter Pruning with Optuna: Efficient Machine Learning OptimizationFinding the right hyper-parameters for your model can be a time-consuming and computationally expensive process. Optuna is a powerful…Aug 23Aug 23
Krishna PullakandamMastering Attention Masking in Neural Networks: A Deep DiveIn the field of natural language processing (NLP) transformer models have become a cornerstone. A critical component of these models is the…Jun 28Jun 28
Krishna PullakandamUnderstanding Precision, Recall, and F-Score at K in Recommender SystemsTL; DRJun 21Jun 21
Krishna PullakandamGuide to Clustering Algorithms: Strengths, Weaknesses, and EvaluationClustering is an unsupervised learning technique used to group similar data points based on certain criteria. It finds applications in…Feb 26Feb 26
Krishna PullakandamRetrieval-Augmented Generation (RAG): Boosting Accuracy and Trust in LLMsLarge language models (LLMs) are everywhere these days. They power the chatbots, the articles we read, and even the creative writing that…Jan 30Jan 30
Krishna PullakandamDeciphering the Dance of Words: Causal Language Modeling Unveils the Causality in TextFor centuries, humans have developed language, weaving meaning, and narratives using words. We understand not just the surface layers of…Jan 18Jan 18
Krishna PullakandamThe Next Chapter: Generative AI and the Dawn of Interactive StorytellingFor millennia, stories have been the threads that bind humanity, transporting us to fantastical worlds, stirring our emotions, and shaping…Dec 20, 2023Dec 20, 2023
Krishna PullakandamStreaming LLMs: Expanding Language Models with Attention SyncThe challenge of feeding large language models with an unlimited amount of data has been a persistent challenge in the world of artificial…Oct 24, 2023Oct 24, 2023
