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5 Beginner-Friendly Projects to Learn LLMs & RAG
I believe in the 'learning by doing' approach—you learn more this way.
Fine-Tuning DistilBERT for Question Answering
This post is divided into three parts; they are: • Fine-tuning DistilBERT for Custom Q&A • Dataset and Preprocessing • Running the Training The...
Understanding the DistilBart Model and ROUGE Metric
This post is in two parts; they are: • Understanding the Encoder-Decoder Architecture • Evaluating the Result of Summarization using ROUGE DistilBart is a...
Creating Powerful Ensemble Models with PyCaret
Machine learning is changing how we solve problems.
Understanding Probability Distributions for Machine Learning with Python
In machine learning, probability distributions play a fundamental role for various reasons: modeling uncertainty of information and data, applying optimization processes with stochastic settings,...
RAG Hallucination Detection Techniques
Large language models (LLMs) are useful for many applications, including question answering, translation, summarization, and much more, with recent advancements in the area having...
A Gentle Introduction to Attention and Transformer Models
This post is divided into three parts; they are: • Origination of the Transformer Model • The Transformer Architecture • Variations of the Transformer...
Building a Recommender System From Scratch with Matrix Factorization in Python
In this article, we will build step by step a movie recommender system in Python, based on matrix factorization.
Natural Language Generation Inside Out: Teaching Machines to Write Like Humans
Natural language generation (NLG) is an enthralling area of artificial intelligence (AI) , or more specifically of natural language processing (NLP) , aimed at...
5 Tips for Avoiding Common Rookie Mistakes in Machine Learning Projects
It's easy enough to make poor decisions in your machine learning projects that derail your efforts and jeopardize your outcomes, especially as a beginner.
