My Journey into Prompt Engineering When I first began exploring language models, I assumed it was as simple as posing a question and waiting for an answer. To my surprise, the initial results were hit or miss. Sometimes I would get insightful responses, while other times the model seemed to completely miss the mark. Understanding … Read more
What is Multiprocessing? Multiprocessing in Python is a means to achieve parallelism, allowing for concurrent execution of processes. It’s a method to exploit multiple processors on a machine, thus making the best use of available CPU cores. Python’s multiprocessing module facilitates this by spawning multiple processes, bypassing the limitations of the Global Interpreter Lock (GIL) … Read more
Introduction to Bayesian Method The Bayesian approach is a probabilistic method of statistical inference, contrasting with the frequentist approach. At its core, Bayesian thinking involves updating the probability estimate for a hypothesis as more evidence or data becomes available. It combines prior beliefs (prior probabilities) with observed data (likelihood) to get posterior probabilities. Bayesian Inference … Read more
What is a Feature Store? At its core, a feature store is a systematized repository specifically tailored for machine learning (ML) features. Features, which are derived or raw data attributes, play a crucial role in the ML model training process. A feature store centralizes the management, storage, and retrieval of these features, ensuring they’re consistently … Read more
Introduction to FastAPI for ML FastAPI is a modern, high-performance web framework written in Python. Its compatibility with Python’s type hints, asynchronous operations, and built-in validation makes it a popular choice for serving machine learning (ML) models. Why Choose FastAPI for ML Serving? FastAPI provides a rapid development environment, ensuring: Key Optimization Techniques Asynchronous Endpoints … Read more
