Applied AI Research for Legal Practitioners

Joshua Escoto | LegalEngineering.AI | Recommended Books

Recommended Books

Bouchard & Peters (2024). Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG.

Ananthaswamy (2024). Why Machines Learn: The Elegant Math Behind Modern AI.

Ascoli (2022). Artificial Intelligence and Deep Learning with Python: Every Line of Code Explained.

Kneusel (2022). Math for Deep Learning: What You Need to Know to Understand Neural Networks.

Tunstall, von Werra & Wolf (2022). Natural Language Processing with Transformers.

Glassner (2021). Deep Learning: A Visual Approach.

Kneusel (2021). Practical Deep Learning: A Python-Based Introduction.

Serrano (2021). Machine Learning.

Howard & Gugger (2020). Deep Learning for Coders with fastai and PyTorch.

Rao & McMahan (2019). Natural Language Processing with PyTorch.

Bird, Klein & Loper (2009). Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit.

Manning & Schutze (1999). Foundations of Statistical Natural Language Processing.