Remove Decision Trees Remove Exploratory Data Analysis Remove Supervised Learning
article thumbnail

Five machine learning types to know

IBM Journey to AI blog

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

article thumbnail

Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data. There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning.

professionals

Sign Up for our Newsletter

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

article thumbnail

Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

Statistical Concepts A strong understanding of statistical concepts, including probability, hypothesis testing, regression analysis, and experimental design, is paramount in Data Science roles. This theorem is crucial in inferential statistics as it allows us to make inferences about the population parameters based on sample data.

article thumbnail

Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Exploratory Data Analysis (EDA): Analysing and visualising data to discover patterns, identify anomalies, and test hypotheses.

article thumbnail

Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Explain the difference between supervised and unsupervised learning. What are the advantages and disadvantages of decision trees ?