The Little Book of Deep Learning

N/A

# link_2d5jdgoyy0c.pdf ## Metadata - PDFFormatVersion=1.5 - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Author=François Fleuret - Title=The Little Book of Deep Learning - Subject=A short introduction to deep learning for readers with a STEM background. It aims at providing the necessary context to understand key AI models for image generation and language processing. - Creator=pdflatex - Producer=LaTeX and TikZ - Keywords=deep learning,machine learning,computer vision,natural language processing - CreationDate=D:20

saved by

• abinaya dinesh
• Ratan Kaliani
• Aryan Naik
• Eddie Sun
• Atem Aguer
• Benedict Neo
• Saloni Shenoy

related reading

• Neural networks and deep learningneuralnetworksanddeeplearning.com
• Understanding Deep Learningudlbook.github.io
• The Decade of Deep Learning | Leo Gaobmk.sh
• Scaling Laws, Carefully | Lil'Loglilianweng.github.io
• NL.pdfabehrouz.github.io
• frontier model training methodologies | Alex Wa's Blogdjdumpling.github.io
• 2404.17625arxiv.org
• Aman's AI Journal • Primers • Ilya Sutskever's Top 30aman.ai
• microgptkarpathy.github.io
• Reiner Pope – The math behind how LLMs are trained and serveddwarkesh.com
• A Theory of Deep Learning | Elements of a Vector Spaceelonlit.com
• [2604.21691] There Will Be a Scientific Theory of Deep Learningarxiv.org