Ai Cheat Sheet
Ai Cheat Sheet
Ai Cheat Sheet
Ai Cheat Sheet
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Statistics ↓↑
Types of Measure
Population and Sample
Outliers
Variance
Standard Deviation
Skewness
Percentiles
Deciles
Quartiles
Box and Whisker Plots
Correlation and Covariance
Hypothesis Test
P Value
Statistical Significance
Bootstrapping
Confidence Interval
Central Limit Theorem
F1 Score (F Measure)
ROC and AUC
Random Variable
Expected Value
Central Limit Theorem
Probability ↓↑
What is Probability
Joint Probability
Marginal Probability
Conditional Probability
Bayesian Statistics
Data Science ↓↑
Probability Distribution
Bernoulli Distribution
Uniform Distribution
Binomial Distribution
Poisson Distribution
Normal Distribution
T-SNE
Data Engineering ↓↑
Data Science vs Data Engineering
Vector and Matrix
Vector
Matrix
Machine Learning ↓↑
L1 and L2 Loss Function
Linear Regression
Logistic Regression
Naive Bayes Classifier
Deep Learning ↓↑
Machine Learning vs Deep Learning
Bias
Activation Function
Natural Language Processing ↓↑
Linguistics and NLP
Text Augmentation
Computer Vision ↓↑
Object Localization
Object Detection
Bounding Box Prediction
Evaluating Object Localization
Anchor Boxes
YOLO Algorithm
R-CNN
Face Recognition
Reinforcement Learning
Reinforcement Learning
System Design
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Interview Questions ↓↑
Questions by Shared Experience
Contact
My Personal Website
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Personal Curated Collection of AI Terminologies from Different Sources with References
Here are the articles in this section:
Statistics ↓↑
Probability ↓↑
Data Science ↓↑
Data Engineering ↓↑
Vector and Matrix
Machine Learning ↓↑
Deep Learning ↓↑
Natural Language Processing ↓↑
Computer Vision ↓↑
Reinforcement Learning
System Design
Interview Questions ↓↑
Contact
Next - Statistics ↓↑
Types of Measure
Last updated
7 months ago
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