Supervised learning is a type of machine learning in which an algorithm learns to map input data to corresponding output labels based on a labeled training dataset.
Unsupervised learning is a type of machine learning where an algorithm learns patterns and structures in input data without being explicitly provided with labeled output.
Following LLMs are publicly available for anyone to use, study, or modify. They are usually trained on large datasets of text from various sources and domains.
A vector database is a type of database that stores data as high-dimensional vectors, which are mathematical representations of features or attributes.
By understanding the basics of AI and ML, we can begin to explore the many opportunities and challenges that these technologies present.
AI model training involves performing complex mathematical computations on large datasets. These computations are typically carried out….