
Build a Large Language Model (From Scratch)
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Narrated by:
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Julie Brierley
About this listen
Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!
In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.
This book teaches you how to:
+ Plan and code all the parts of an LLM
+ Prepare a dataset suitable for LLM training
+ Fine-tune LLMs for text classification and with your own data+ Use human feedback to ensure your LLM follows instructions
+ Load pretrained weights into an LLMBuild a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI.
As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.
About the book: This is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself!
About the listener: Listeners need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs.
About the author: Sebastian Raschka is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
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- Narrated by: Daniel Henning
- Length: 11 hrs and 42 mins
- Unabridged
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In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine-tuning.
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No added pdf
- By Anonymous User on 06-11-25
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Fundamentals of Artificial Intelligence & Large Language Models
- Master Prompt Engineering and Monetize the Power of Language Processing
- By: Russell Dawson
- Narrated by: Dan Hamel
- Length: 4 hrs and 33 mins
- Unabridged
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Curious about AI, but unsure how it works? Want to tap into the lucrative potential of this rapidly advancing technology? Unlock the immense potential of AI with this transformative book! Welcome to Fundamentals of Artificial Intelligence & Large Language Models, the second in a series of books crafted to help you join a movement toward a more financially fruitful future.
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Mastered AI Basics
- By Evie on 06-17-25
By: Russell Dawson
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Designing Machine Learning Systems
- An Iterative Process for Production-Ready Applications
- By: Chip Huyen
- Narrated by: Kathleen Li
- Length: 15 hrs
- Unabridged
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Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.
By: Chip Huyen
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Fundamentals of Data Engineering
- Plan and Build Robust Data Systems
- By: Joe Reis, Matt Housley
- Narrated by: Adam Verner
- Length: 17 hrs and 31 mins
- Unabridged
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Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
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Great for Hands on Business owners
- By LmL on 08-14-24
By: Joe Reis, and others
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Database Internals
- A Deep Dive into How Distributed Data Systems Work, 1st Edition
- By: Alex Petrov
- Narrated by: Mike Chamberlain
- Length: 12 hrs and 51 mins
- Unabridged
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When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.
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I can't believe this exists as an audiobook.
- By Michael Marcin on 12-18-23
By: Alex Petrov
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Deep Learning with Python
- By: Francois Chollet
- Narrated by: Mark Thomas
- Length: 9 hrs and 55 mins
- Unabridged
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Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this audiobook builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
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Almost Perfect - Better when paired with the book
- By Graham on 10-30-18
By: Francois Chollet
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Machine Learning Bookcamp
- Build a Portfolio of Real-Life Projects
- By: Alexey Grigorev
- Narrated by: Adam Newmark
- Length: 8 hrs and 49 mins
- Unabridged
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In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see.
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Good but I mixed ebook + audio book
- By JUAN CARLOS MARTINEZ LOERA on 10-27-24
By: Alexey Grigorev
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Software Architecture: The Hard Parts
- Modern Trade-Off Analyses for Distributed Architectures
- By: Neal Ford, Mark Richards, Pramod Sadalage, and others
- Narrated by: Dena Dahilig
- Length: 12 hrs and 53 mins
- Unabridged
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There are no easy decisions in software architecture. Instead, there are many hard parts—difficult problems or issues with no best practices—that force you to choose among various compromises. With this book, you'll learn how to think critically about the trade-offs involved with distributed architectures. Architecture veterans and practicing consultants Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani discuss strategies for choosing an appropriate architecture.
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Great content. Terrible narration.
- By Alex on 12-16-23
By: Neal Ford, and others
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Prompt Engineering for Generative AI
- Future-Proof Inputs for Reliable AI Outputs
- By: James Phoenix, Mike Taylor
- Narrated by: Mike Chamberlain
- Length: 11 hrs and 6 mins
- Unabridged
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Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice.
By: James Phoenix, and others
Expensive for the content
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Really hard to follow when everything is see code
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Don’t waste your money on the Audible version
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Hard to follow when every other sentence “see code”. Some books don’t convey well in audio
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