February 24, 2025
Updated July 15, 2025
11 minute read
An Introduction to DeepSeek
In the rapidly expanding universe of artificial intelligence, a new name has been making significant waves: DeepSeek. A private Chinese AI company founded in July 2023, DeepSeek has quickly positioned itself as a major contender in the development of large language models (LLMs). Backed by the Chinese hedge fund High-Flyer, the company has distinguished itself through a commitment to creating powerful, open-weight models that challenge the performance of established industry leaders, often at a fraction of the training cost. This approach has not only captured the attention of developers and researchers but has also sent ripples through the global tech market.
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Find a path to becoming a DeepSeek. Learn more at:
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Reading list
We've selected 33 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
DeepSeek.
Provides a practical, hands-on approach to understanding and implementing Transformer models, which are the core architecture behind most large language models, including DeepSeek. Co-authored by Hugging Face engineers, it's highly relevant for anyone looking to work with or understand the technical underpinnings of modern LLMs. The revised edition valuable and up-to-date resource.
Offers a unique perspective by guiding the reader through the process of building an LLM from the ground up. This hands-on approach provides a deep understanding of the internal workings of these models, which is highly relevant to comprehending how DeepSeek is built and trained.
This foundational textbook in the field of deep learning, covering a wide range of topics from basic concepts to advanced techniques. It is essential for gaining a broad understanding of the neural networks and architectures that underpin models like DeepSeek. While published in 2016, its comprehensive nature makes it a valuable reference and is often used as a textbook in academic institutions.
Offers a comprehensive exploration of Transformer architectures specifically for machine learning tasks. It delves into various Transformer models and their applications beyond just NLP, providing a deeper technical understanding of this crucial architecture.
Focusing specifically on generative models, this book is highly relevant to understanding the capabilities of DeepSeek in generating text and potentially other forms of content. It covers various generative techniques, including Transformers, providing insights into the models that enable creative AI applications. The second edition recent publication.
This recent book delves into the practical aspects of building AI agents using LLMs. Given the course context mentioning AI Agents, this book is highly relevant for understanding how models like DeepSeek can be used to create autonomous and intelligent systems.
A widely recognized and comprehensive textbook covering the fundamentals of Natural Language Processing (NLP). Understanding NLP is crucial for comprehending how models like DeepSeek process and generate human language. provides a strong theoretical foundation and is often used in both undergraduate and graduate NLP courses.
Focuses specifically on Transformer architectures and their applications in NLP. It covers various Transformer models and provides practical guidance on using them. It's a good resource for understanding the specific architecture that makes LLMs powerful.
Another recent publication focusing on the design and implementation of AI agents, including multi-agent systems. provides a more in-depth look at the architectural considerations and practical challenges of building agent-based applications powered by LLMs.
Written by the creator of Keras, this book offers a practical introduction to deep learning using Python. It's known for its clear explanations and hands-on examples, making complex concepts accessible. The second edition is updated and a valuable resource for practitioners.
Co-authored by a co-founder of DeepMind and Inflection AI, this book explores the transformative impact of AI and other frontier technologies on society. It discusses the challenges of controlling powerful technologies like advanced AI, offering a contemporary perspective on the broader implications of developments like DeepSeek.
This textbook presents AI as the study of designing intelligent computational agents, offering a coherent and updated overview of the field. The third edition includes recent AI advances. It provides a solid foundation in AI concepts relevant to building intelligent systems, including those involving language processing.
A very popular and practical guide to machine learning and deep learning. While not exclusively focused on LLMs or generative AI, it provides essential hands-on experience with key libraries and concepts necessary for working with and understanding the models that power DeepSeek. The third edition recent and widely used reference.
Focuses on building applications using LLMs and frameworks like LangChain. It's relevant for understanding how models like DeepSeek can be integrated into practical applications and the ecosystem surrounding them.
Provides a solid understanding of the core concepts and techniques in deep learning. It covers various architectures and applications, offering a good foundation for comprehending the technologies behind advanced AI models like DeepSeek. The second edition recent update.
Bridges the gap between theory and practice, focusing on building real-world NLP systems. It's valuable for understanding how the concepts behind models like DeepSeek are applied in industry and provides practical insights for developing NLP applications.
This widely respected textbook provides a comprehensive introduction to pattern recognition and machine learning from a Bayesian perspective. It covers fundamental concepts that are essential for a deep understanding of the algorithms used in AI models like DeepSeek.
A recent practical guide aimed at making AI agents accessible to a wider audience. It focuses on building and understanding agent-based systems without requiring extensive prior AI knowledge, making it suitable for those interested in the practical applications of models like DeepSeek in creating agents.
This concise book offers a quick and accessible overview of language models, including the concepts behind Transformers and their historical context. It's a good starting point for those who want to quickly grasp the core ideas of LLMs without getting bogged down in excessive detail.
Dives into the details of Transformer models and their application in NLP. It covers building models from scratch, providing a solid technical understanding of the architecture that is fundamental to large language models like DeepSeek. Suitable for those with a strong technical background wanting to master Transformers.
A fundamental text in the field of statistical learning, providing a rigorous treatment of key concepts and techniques used in machine learning. While mathematically intensive, it offers a deep understanding of the statistical foundations relevant to AI model development and analysis.
A widely used introductory book to NLP using the NLTK library in Python. It covers fundamental NLP concepts and techniques with a practical approach. While some topics might be more basic than the advanced models like DeepSeek, it provides a necessary foundation in text processing.
Addresses the critical intersection of AI with security, privacy, and ethics. Given the increasing deployment of powerful AI models, understanding these aspects is vital for responsible development and use. It provides a comprehensive overview of the challenges and considerations in this space.
A classic and foundational text in statistical NLP. While older, the principles covered are still relevant for understanding the mathematical and statistical underpinnings of language modeling. It's more theoretical than practical but provides crucial background knowledge.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/74o2ol/deepsee
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