Remove Clustering Remove EDA Remove Support Vector Machines
article thumbnail

Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset. EDA guides subsequent preprocessing steps and informs the selection of appropriate AI algorithms based on data insights. Popular models include decision trees, support vector machines (SVM), and neural networks.

article thumbnail

Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

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. Here is a brief description of the same.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Enhancing Customer Churn Prediction with Continuous Experiment Tracking

Heartbeat

Load and Explore Data We load the Telco Customer Churn dataset and perform exploratory data analysis (EDA). EDA is essential for gaining insights into the dataset’s characteristics and identifying any data preprocessing requirements. Are there clusters of customers with different spending patterns? #3.

article thumbnail

Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

C Classification: A supervised Machine Learning task that assigns data points to predefined categories or classes based on their characteristics. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.