Author(s): Boris Meinardus Originally published on Towards AI. How do you best learn Data Science and then get a Job? How long does it take, and how much does it cost? What is data science??? There are so many questions you guys …

Author(s): Youssef Hosni Originally published on Towards AI. Prompt Engineering for Instruction-Tuned LLM Large language models excel at translation and text transformation, effortlessly converting input from one language to another or aiding in spelling and grammar corrections. They are adept at taking …

Author(s): Meng Li Originally published on Towards AI. Created by Meng Li Large models are really popular right now, but they can be quite expensive to use! However, I’ve found some cost-saving methods that I’d like to share with everyone. Firstly, we …

Author(s): Youssef Hosni Originally published on Towards AI. Retrieval-Augmented Generation (RAG) is the concept of providing large language models (LLMs) with additional information from an external knowledge source. This allows them to generate more accurate and contextual answers while reducing hallucinations. In …

Author(s): Eivind Kjosbakken Originally published on Towards AI. This article teaches you how to approach and solve a data science project by examining the prediction of UFC fight outcomes. This article will feature how to make accurate classification predictions for the outcome …

Author(s): ___ Originally published on Towards AI. Using Your Data To Build Reasoning Chains 🧠⛓️ Retrieval Augmented Generation (RAG) typically finds its place in enhancing document-based question answering (QnA), effectively leveraging extensive databases to provide contextually relevant information for Large Language Models …

Author(s): Youssef Hosni Originally published on Towards AI. Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article summarizes some of the …