Introduction to Neural Networks and PyTorch Neural networks are a subset of machine learning models inspired by the human brain’s structure. Comprising interconnected nodes or neurons, these networks are designed to recognize patterns and solve complex tasks, such as image classification, natural language processing, and more. Each neuron receives input, processes it using…
Introduction to Explainable AI As artificial intelligence (AI) technologies become integral to a plethora of industries, the importance of Explainable AI (XAI) emerges paramount. Explainable AI refers to methodologies and techniques that make the outputs of AI systems understandable to humans. This growing field aims to foster transparency in AI decision-making, an essential…
Introduction to AI Language Models Artificial Intelligence (AI) language models have emerged as pivotal tools in the realm of natural language processing (NLP). These sophisticated algorithms are designed to understand, generate, and manipulate human language, enabling machines to interact with users in a more intuitive manner. From their inception, AI language models have…
Introduction to Reinforcement Learning Reinforcement Learning (RL) is a subfield of machine learning characterized by an agent’s ability to learn how to achieve a goal by interacting with its environment. Unlike traditional paradigms such as supervised learning, where the model is trained on a labeled dataset, or unsupervised learning, where the model attempts…
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