HMM applications

Hidden Markov Models (HMMs) are statistical tools used to analyze systems that change over time but are not directly observable. They have various applications, such as speech recognition, where they help interpret spoken words by modeling sound patterns. In finance, HMMs predict market trends by analyzing historical data. They’re also utilized in bioinformatics for gene prediction, recognizing patterns in DNA sequences. Essentially, HMMs provide a framework for understanding complex processes by observing their outcomes and inferring the hidden states that drive these changes.