Rex W. Douglass PhD
Projects
ML and Stats Notes
Résumé
Chapters
Algebra
Dot product
Algorithms
Search Algorithms
Sorting Algorithms
Arithmetic
Addition
Division
Equality
Exponent
Integer Division
Modulo
Multiplication
Subtraction
Calculus
Automatic Differentiation
Derivative
Calibration
Calibration
Conformal Prediction
Causality
Collapsibility
Compliance
Consistency
Correct model specification
Missing Data Mechanism
No conditioning on a collider
No conditioning on Mediators
No Interference
No Relevant Effect Modification
No Relevant Measurement Error
No unmeasured confounders
Positivity
Recoverability
Testability
Transparency
Communication
Markdown
Computation
O-notation
Parallelization
Vectorization
Control Flow
If / Else / Where
Data
Imagery
Tabular
Text
Data Loading
Data Loaders (for GPU)
Data Transformation
Filter
Fuzzy Recording Matching
Joins
Regex
Slicing
Databases
Arrow
DuckDB
Postgres
Domain
External Validity
Internal Validity
Matching
Outcome regressions / Response Surface Modeling
Outliers
Poststratification
Regime Change
Transportability
Estimation
Asymptotics
Bayesianism
Bias
Bias Variance Tradeoff
Frequentism
Out of Sample Performance
P Values
Performance
Regularization
Variance
Hypothesis Testing
{.unnumbered}
Critiques of Hypothesis Testing
Hypothesis Testing
Statistical Power
Wilcoxon signed-rank test
Identification Strategies
Difference in Difference
Double / Debiased ML
Fixed Effects
Granger Causality
Instrumental Variables
Placebo Tests
Random Control Trials
Regression Discontinuity (RDD)
Synthetic Controls
Images
Annotating Images
Remote Sensing
You Only Look Once (Yolo)
Industry
Case Studies
Companies
Gossip
Interview Questions
Jobs
Practice Coding
Salaries
Languages
Bash
Git
jax
Numpyro
pyro
Python
R
SQL
Stan
tensorflow
Likelihood
Likelihood Function
Maximum Likelihood Estimation (MLE)
Literature
Broad Literature
Finding Papers
Information Theory
Overview Literature
Statistics Literature
Logic
And
Or
Math and Data Structures
Boolean
Dictionary
Floating Point Numbers (Floats)
Function
Graphs
Hash Table
Jobs
Linked Lists
List (Sequence)
NaN (Not a Number)
NULL
Set
Stacks and Queues
Table
Trees
Vector / Matrix / Tensor
Measurement
Data Reliability
Data Validity
Meta Science
Meta Reviews
Null Results
Open Science
Replicability
Sociology of Inference
Multilevel Modeling
1-way Fixed Effecs
2-way Fixed Effects
Fully Pooled
random effects
Neural Networks
Contrastive Learning
Curriculum Learning
Neural Network Debugging
Self-prediction
Probability
Entropy
Maximum Entropy Distribution
Mean
Normal Distribution
Poisson
Probability Case Studies
Probability distribution
Probability Mass/Density Function (PMF/PDF)
Production
Deployment
Monitoring Experiments
Random Variables
Exchangeable
Independent and identically distributed random variables (IID)
Random Variable
Reinforcement Learning
Reinforcement Learning
Research Design
Backdoor Adjustment
Confounder
Estimand
Garden of Forking Paths
Identification
Potential Outcomes
Project Design
Research Design Directed Acyclic Graphs (DAGs)
Unit of Analysis
Unobserved Confounding
Statistics
Consistency
Domain / Generalizability / Transportability
Efficiency
Population
Sufficiency
Variation
Supervised Learning
Decision Trees
Gaussian Processes
Gradientboosting
Interactions
OLS
Random Forest
Survival
Survival Models
Text
Large Language Models (LLM)
Time Series
Kalman Filter
Unsupervised Learning
Distance Metrics
Hierarchical Clustering
K-means Clustering
Contents
1
K-means Clustering
1
K-means Clustering
K Means Clustering Algorithm | K Means In Python | Machine Learning Algorithms |Simplilearn
Hierarchical Clustering