Welcome to Tobin's Tools! I'm Kyle Tobin, I'm an IT leader with experience in systems engineering, software development, cloud architecure, product management, and IT business processes. This repository is a collection of educational resources that cover various topics related to IT all of which are publicly accessible.
All resources in Tobin's Tools are licensed under the Educational Community License v2.0 (ECL-2.0), which means you're free to use, copy, modify, and distribute the materials for any purpose, whether personal, academic, or commercial, as long as you give appropriate credit and share any modifications under the same license terms.
Please note that Tobin's Tools is a work in progress, and I'll be adding new materials over time. If you have suggestions or feedback, please feel free to create an issue or pull request.
This content provides an introduction to the key concepts and technologies behind LLM powered chatbot development, including the Transformer algorithm, Large Language Models, Natural Language Processing, Natural Language Understanding, and Natural Language Generation.
Machine Learning 101 is a comprehensive guide for IT engineers and cloud architects new to data science and machine learning. The guide covers fundamental concepts, techniques, and algorithms, with sections on introduction to machine learning, popular algorithms, neural networks and deep learning, natural language processing, model evaluation and validation, feature engineering and selection, and advanced topics. By the end, readers will have a In this easy-to-follow guide, we'll walk you through the process of setting up and starting the training of a transformer-based large language model (LLM). Don't worry if you're new to this field; we'll break down each step for you, ensuring you'll have a solid understanding of how to configure and initiate your very own LLM training. So, let's get started on this exciting journey of creating powerful language models! this easy-to-follow guide, we'll walk you through the process of setting up and starting the training of a transformer-based large language model (LLM). Don't worry if you're new to this field; we'll break down each step for you, ensuring you'll have a solid understanding of how to configure and initiate your very own LLM training. So, let's get started on this exciting journey of creating powerful language models!id foundation in machine learning and be prepared to explore more advanced topics and apply techniques to real-world problems.Machine Learning 101 is a comprehensive guide for IT engineers and cloud architects new to data science and machine learning. The guide covers fundamental concepts, techniques, and algorithms, with sections on introduction to machine learning, popular algorithms, neural networks and deep learning, natural language processing, model evaluation and validation, feature engineering and selection, and advanced topics. By the end, readers will have a solid foundation in machine learning and be prepared to explore more advanced topics and apply techniques to real-world problems.
In this easy-to-follow guide, we'll walk you through the process of setting up and starting the training of a transformer-based large language model (LLM). Don't worry if you're new to this field; we'll break down each step for you, ensuring you'll have a solid understanding of how to configure and initiate your very own LLM training. So, let's get started on this exciting journey of creating powerful language models!
This project is licensed under the Educational Community License v2.0 (ECL-2.0).
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This software, documentation, and other materials are provided "as is" without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and non-infringement. In no event shall the Licensor be liable for any claim, damages, or other liability, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the software, documentation, or other materials.
To view a copy of the full license, visit https://opensource.org/licenses/ECL-2.0 or see the LICENSE file in the root directory of this repository.