V8
/veɪt/
noun … “a high-performance JavaScript and WebAssembly engine.”
V8 is a high-performance execution engine designed to run JavaScript and WebAssembly code efficiently and at scale. It is best known as the engine that powers modern web browsers like Google Chrome, but its influence extends far beyond the browser into servers, embedded systems, and tooling ecosystems.
State Management
/steɪt ˈmæn.ɪdʒ.mənt/
noun … “keeping your application’s data in order.”
Surface Integral
/ˈsɜːr.fɪs ˈɪn.tɪ.ɡrəl/
noun … “summing quantities over a curved surface.”
Flux
/flʌks/
noun … “flow that carries change.”
Bootstrap
/ˈbuːt.stræp/
noun … “resampling your way to reliability.”
Hidden Markov Model
/ˈhɪd.ən ˈmɑːrkɒv ˈmɒd.əl/
noun … “seeing the invisible through observable clues.”
Hidden Markov Model (HMM) is a statistical model that represents systems where the true state is not directly observable but can be inferred through a sequence of observed emissions. It extends the concept of a Markov Process by introducing hidden states and probabilistic observation models, making it a cornerstone in temporal pattern recognition tasks such as speech recognition, bioinformatics, natural language processing, and gesture modeling.
Naive Bayes
/naɪˈiːv ˈbeɪz/
noun … “probabilities, simplified and fast.”
Naive Bayes is a probabilistic machine learning algorithm based on Bayes’ theorem that assumes conditional independence between features given the class label. Despite this “naive” assumption, it performs remarkably well for classification tasks, particularly in text analysis, spam detection, sentiment analysis, and document categorization. The algorithm calculates the posterior probability of each class given the observed features and assigns the class with the highest probability.
Singular Value Decomposition
/ˈsɪŋ.ɡjʊ.lər ˈvæl.ju dɪˌkɑːm.pəˈzɪʃ.ən/
noun … “disassembling a matrix into its hidden building blocks.”
Kernel Function
/ˈkɜːr.nəl ˈfʌŋk.ʃən/
noun … “measuring similarity in disguise.”
Kernel Trick
/ˈkɜːr.nəl trɪk/
noun … “mapping the invisible to the visible.”