Daily update | 08 December, 2021
Medium
A Complete 26 Week Course to Learn Python for Data Science in 2022
Author: Frank Andrade
Claps: 112
Source: machine-learning
Description: Learn most of the Python stuff you need for data science in 26 weeks
Drift Metrics: How to Select the Right Metric to Analyze Drift
Author: Piotr (Peter) Mardziel
Claps: 52
Source: machine-learning
Description: In our last post we summarized the problem of drift in machine learning deployments (“Drift in Machine Learning: Why It’s Hard and What to…
MANTA Test
Author: Matrix AI Network
Claps: 50
Source: machine-learning
Description: 9–11 December
Introduction to Applied Linear Algebra: Norms & Distances
Author: Deniz Tuzsus
Claps: 15
Source: data-science
Description: This article gives an introduction to vector norms, vector distances and their application in the field of data science
Self-Training Classifier: How to Make Any Algorithm Behave Like a Semi-Supervised One
Author: Saul Dobilas
Claps: 14
Source: data-science
Description: An easy Python implementation of Self-Training using standard classification algorithms from the Sklearn library
StackExchange
One Sample T-Test - Data Transformation
Source: stats
Views: 42
Score: 3
Tags: t-test lognormal-distribution
Gaussian Processes: multi-class Laplace approximation
Source: stats
Views: 17
Score: 2
Tags: covariance-matrix gaussian-process
Correct use of Chi-square and hypothesis testing?
Source: stats
Views: 28
Score: 2
Tags: hypothesis-testing statistical-significance python chi-squared-test experiment-design
Why is deviance != -2 logLik for logistic regression in R?
Source: stats
Views: 13
Score: 2
Tags: logistic likelihood deviance
Some questions about supervised learning, model evaluation and preprocessing
Source: datascience
Views: 27
Score: 2
Tags: classification class-imbalance preprocessing supervised-learning multilabel-classification