algorithms
Algorithm Design Manual - book notes
Algorithms for Decision Making - book notes
Bandit Algorithms
Book chapter summaries - deep learning, machine learning, various math
Clever (Ruby) Algorithms
Clustering
Compiler Theory - book notes
Essential Reads (7/22/19) (updated)
Essential Reads - 8/15/2019
Linear Algebra, Machine Learning, Deep Learning articles (originally posted Dec2019)
Math (ML,DL,algos,prob,stats,...) Resources
Pricing algorithms & collusion
Sorting (ADM)
Stuff to Read, 12/14/21 (revisited)
Understanding backward passes
deep-learning
Activation function articles
Book chapter summaries - deep learning, machine learning, various math
CMOS Dec'2019
Computer Vision booknotes
DL with Python & DL with PyTorch - book notes
Deep Learning - Goodfellow book notes (2019)
Deep Learning / Data Science / Machine Learning / Probability / Stats - Dec'2019
Dive into Deep Learning ebook
Essential Reads - July 2019
Facial Recognition - Types of Attacks and Anti-Spoofing Techniques
GANs (Venture Beat, Floydhub)
Glossary of adversarial nets / GANs articles
Kornia - Pytorch vision library
LLM - large language model) survey - ArXiV
Linear Algebra, Machine Learning, Deep Learning articles (originally posted Dec2019)
ML Cheatsheet (pdf)
Math (ML,DL,algos,prob,stats,...) Resources
NLP - December 2019
New approaches to Object Detection
Object Detection - An End to End Theoretical Perspective
Papers with Code
Papers with code | SOTA
Pose Estimation Techniques
Real-Time Hand Tracking with MediaPipe (GoogleBlog)
Semantic Segmentation
Stuff to Read, 12/14/21 (revisited)
Transformer models - intro and catalog
Understanding backward passes
Up-sampling with Transposed Convolutions
What is Targeted Dropout?
machine-learning
Activation function articles
Activations (Machine Learning)
Algorithm Design Manual - book notes
Bandit Algorithms
Book chapter summaries - deep learning, machine learning, various math
Clustering
Data Science Interview Q&A
Data Structures (ADM)
Deep Learning / Data Science / Machine Learning / Probability / Stats - Dec'2019
Elements of Statistical Learning - book notes
Essential Reads (8/2/2019)
Essential Reads - 8/15/2019
Essential Reads - July 2019
Feature Engineering Articles (2019)
Insurance Pricing with Tweedie
Linear Algebra, Machine Learning, Deep Learning articles (originally posted Dec2019)
ML Cheatsheet (pdf)
ML project from scratch
Math (ML,DL,algos,prob,stats,...) Resources
Milvus open-source vector similarity search engine
Paperspace Gradient Notebook
Pycaret Links
Python resources
R language resources
Scikit-Learn Guide notes
Seaborn gallery
Sorting (ADM)
Statistics for Data Science - booknotes
Stuff to Read, 12/26/2021 (revisited)
Understanding backward passes
Social Media in China Survey - 2020
Twitter's Agency Playbook