Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. What is cross-validation, and why is it used in Machine Learning?

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

Iguazio

JUNE 25, 2023

Clustering Metrics Clustering is an unsupervised learning technique where data points are grouped into clusters based on their similarities or proximity. Evaluation metrics include: Silhouette Coefficient - Measures the compactness and separation of clusters.

ML 52

ML ML Clustering Cross Validation 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 Deep Learning Deep Learning 52

The MLOps Blog

JUNE 6, 2023

This is an ensemble learning method that builds multiple decision trees and combines their predictions to improve accuracy and reduce overfitting. Perform cross-validation using StratifiedKFold. The model is trained K times, using K-1 folds for training and one fold for validation. Create the ML model.

ML 52

ML ML Cross Validation Machine Learning 52

DagsHub

APRIL 21, 2024

It offers implementations of various machine learning algorithms, including linear and logistic regression , decision trees , random forests , support vector machines , clustering algorithms , and more. There is no licensing cost for Scikit-learn, you can create and use different ML models with Scikit-learn for free.

Machine Learning 59

Machine Learning Machine Learning ML ML 59