Mostafa Ibrahim

Learn about the history of LLMs, including the groundbreaking GPT series and how they work, and explore developments like human-guided reinforcement learning.

A deep dive into question answering in machine learning, examining its challenges, techniques, and models, along with a step-by-step Python code illustration.

This article provides an A-to-Z guide to how Transformer Networks function, and discusses why they outperform neural network models such as LSTM and RNN.

In this article, we cover the basics of sequence classification, its applications, and how it uses LSTMs, all alongside an implementation of a TensorFlow machine.

In this article, we explore the benefits, challenges, and future of text summarization technology, including the most popular algorithms and their limitations.

This article explores the integration of LlamaIndex and Weights & Biases for developing efficient QA systems, providing step-by-step guidance and highlighting their benefits in natural language processing applications.

A beginner's guide to audio classification with Keras, covering the audio classification process, and the basics of identifying and categorizing different types of sound.

This article explores extractive question answering using HuggingFace Transformers, PyTorch, and W&B. Learn how to build a SOTA question-answering model.

This article explores Named Entity Recognition (NER) using HuggingFace, PyTorch, and W&B. It covers the process of training a model on the CoNLL2003 dataset and performing NER on example sentences.

Understand machine learning better with our guide on accuracy and loss curves. We explain their differences, how to read them, and why they're important

This article explores AIOps, MLOps, and LLMOps, including their distinct roles, challenges, and impacts in the evolving, data-driven operations landscape.