A Quick Uplift Modeling Introduction

towardsdatascience.com/a-quick-uplift-modeling-introduction-6e14de32bfe0

Streaming Video Experimentation at Netflix: Visualizing Practical and Statistical Significance

netflixtechblog.com/streaming-video-experimentation-at-netflix-visualizing-practical-and-statistical-significance-7117420f4e9a

Experimentation is a major focus of Data Science across Netflix

netflixtechblog.com/experimentation-is-a-major-focus-of-data-science-across-netflix-f67923f8e985

Netflix Research

research.netflix.com/research-area/experimentation-and-causal-inference

A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix

netflixtechblog.com/a-day-in-the-life-of-an-experimentation-and-causal-inference-scientist-netflix-388edfb77d21

arxiv.org/pdf/1904.07272.pdf

Multi-armed Bandits: an alternative to A/B testing

medium.com/@brunonishimoto/multi-armed-bandits-an-alternative-to-a-b-testing-8acce8e12549

What is Multi-Armed Bandit(MAB) Testing? | VWO

vwo.com/blog/multi-armed-bandit-algorithm/

Matrix Completion for Causal Models

causalinf.substack.com/p/matrix-completion-for-causal-models

1710.10251.pdf

arxiv.org/pdf/1710.10251.pdf

Did Facebook Hurt Our Mental Health? Probably

causalinf.substack.com/p/did-facebook-hurt-our-mental-health

jobs.netflix.com/culture?lang=English

jobs.netflix.com/candidateprivacy

Netflix - Overview - Long-Term View

ir.netflix.net/ir-overview/long-term-view/default.aspx

Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch

sebastianraschka.com/blog/2023/self-attention-from-scratch.html

Transformers from Scratch

e2eml.school/transformers.html

The Illustrated Transformer

jalammar.github.io/illustrated-transformer/

Transformer Architecture: The Positional Encoding - Amirhossein Kazemnejad's Blog

kazemnejad.com/blog/transformer_architecture_positional_encoding/

A.pdf

web.stanford.edu/~jurafsky/slp3/A.pdf

Tutorial — hmmlearn 0.2.8.post29+gba62fed documentation

hmmlearn.readthedocs.io/en/latest/tutorial.html

Logistic Regression with PyTorch

towardsdatascience.com/logistic-regression-with-pytorch-3c8bbea594be

Study Note: Comparing Logistic Regression, LDA, QDA, and KNN

nancyyanyu.github.io/posts/6084c2b2/

A Deep Markov Model for Clickstream Analytics in Online Shopping

dl.acm.org/doi/fullHtml/10.1145/3485447.3512027

Deep Learning Optimizers

towardsdatascience.com/deep-learning-optimizers-436171c9e23f

Linear Discriminant Analysis

sebastianraschka.com/Articles/2014_python_lda.html

Machine Learning Models | Descriptive & Generative ML Models

www.analyticsvidhya.com/blog/2021/07/deep-understanding-of-discriminative-and-generative-models-in-machine-learning/

Teaching Your Own Kids To Ski: 5 Critical Skills To Teach

skiingkids.com/teaching-your-own-kids-to-ski/

7 Best Kids Ski Harnesses, Proper Use + HARNESS WARNING!

skiingkids.com/best-kids-ski-harnesses/

Linear Discriminant Analysis, Explained

towardsdatascience.com/linear-discriminant-analysis-explained-f88be6c1e00b

14.3 - Discriminant Analysis | STAT 555

online.stat.psu.edu/stat555/node/101/

Discriminant Analysis Essentials in R - Articles - STHDA

www.sthda.com/english/articles/36-classification-methods-essentials/146-discriminant-analysis-essentials-in-r/

ML | Linear Discriminant Analysis - GeeksforGeeks

www.geeksforgeeks.org/ml-linear-discriminant-analysis/

Bayesian Inference and Transformers

towardsdatascience.com/bayesian-inference-and-transformers-3dc473ac1af2

PyTorch简明教程 - 李理的博客

fancyerii.github.io/books/pytorch/

人工智能 LLM 革命前夜：一文读懂横扫自然语言处理的 Transformer 模型

zhuanlan.zhihu.com/p/601392771?utm_campaign=shareopn&utm_medium=social&utm_oi=1396073146395553792&utm_psn=1607543625260511232&utm_source=wechat_timeline&utm_id=0https://zhuanlan.zhihu.com/p/601392771?utm_campaign=shareopn&utm_medium=social&utm_oi=1396073146395553792&utm_psn=1607543625260511232&utm_source=wechat_timeline&utm_id=0

Illustrated Guide to LSTM’s and GRU’s: A step by step explanation

towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-by-step-explanation-44e9eb85bf21

Activation Functions: Sigmoid vs Tanh | Baeldung on Computer Science

www.baeldung.com/cs/sigmoid-vs-tanh-functions

Activation Functions in Neural Networks

towardsdatascience.com/activation-functions-neural-networks-1cbd9f8d91d6

Training a Classifier — PyTorch Tutorials 1.13.1+cu117 documentation

pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html

Neural Networks — PyTorch Tutorials 1.13.1+cu117 documentation

pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html

ComputationalGraphs/PyTorchCG.ipynb at master · msminhas93/ComputationalGraphs · GitHub

github.com/msminhas93/ComputationalGraphs/blob/master/PyTorchCG.ipynb

Python 子类继承父类构造函数说明 | 菜鸟教程

www.runoob.com/w3cnote/python-extends-init.html

Python 面向对象 | 菜鸟教程

www.runoob.com/python/python-object.html

The “gradient” argument in Pytorch’s “backward” function — explained by examples

zhang-yang.medium.com/the-gradient-argument-in-pytorchs-backward-function-explained-by-examples-68f266950c29

Microsoft Word - learning user real time intent Nov 27 2014 - learninguserrealtimeintentNov272014.pdf

www.researchgate.net/profile/Shibo-Li/publication/271373754_Learning_User_Real-Time_Intent_for_Optimal_Dynamic_Web_Page_Transformation/links/54c6576d0cf219bbe4f82ec9/Learning-User-Real-Time-Intent-for-Optimal-Dynamic-Web-Page-Transformation.pdf

1905.12595.pdf

arxiv.org/pdf/1905.12595.pdf

Shopper intent prediction from clickstream e-commerce data with minimal browsing information - Scientific Reports

www.nature.com/articles/s41598-020-73622-y

F1 score vs AUC, which is the best classification metric?

stephenallwright.com/f1-score-vs-auc/

Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP Analyses

www.aidancooper.co.uk/a-non-technical-guide-to-interpreting-shap-analyses/

A Gentle Introduction to torch.autograd — PyTorch Tutorials 1.13.1+cu117 documentation

pytorch.org/tutorials/beginner/blitz/autograd_tutorial.html