In Build a DeepSeek Model (From Scratch) you’ll build your own DeepSeek clone from the ground up. First, you’ll quickly review LLM fundamentals, with an eye to where DeepSeek’s innovations address the common problems and limitations of standard models. Then, you’ll learn everything you need to create your own DeepSeek-inspired model, including the innovations that put DeepSeek on the map: Multihead Latent Attention (MLA), Multi-Token Prediction (MTP), Mixture of Experts (MoE), model distillation, and reasoning.
Raj Abhijit Dandekar, Rajat Dandekar, Sreedath Panat, Naman Dwivedi
Build a DeepSeek Model (From Scratch) is a hands-on guide to creating your own DeepSeek-style model step by step. You’ll start with a base LLM, then implement reasoning, retrieval, and optimization components to reproduce DeepSeek’s key architectural ideas. It’s an accessible deep dive into how multi-stage inference, reasoning traces, and reinforcement loops come together to create models capable of logical, multi-step problem solving.
In this book, you’ll learn how to:
-
Implement a DeepSeek-style reasoning framework from the ground up
-
Integrate retrieval augmentation, reasoning tokens, and self-reflection
-
Apply reinforcement learning for reasoning improvement
-
Measure reasoning performance across math, logic, and code tasks
-
Understand how reasoning models differ from traditional LLMs
Whether you’re a machine learning engineer, researcher, or developer curious about reasoning-centric AI, Build a DeepSeek Model (From Scratch) offers a transparent, implementation-first look into one of the most exciting frontiers in modern AI.
Don’t forget you can get 45% off with your Devtalk discount! Just use the coupon code “devtalk.com” at checkout 