Pickl AI

FEBRUARY 12, 2024

Statistical Concepts A strong understanding of statistical concepts, including probability, hypothesis testing, regression analysis, and experimental design, is paramount in Data Science roles. Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Techniques such as cross-validation, regularisation , and feature selection can prevent overfitting. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. What are the advantages and disadvantages of decision trees ?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52