Machine learning (ML) is transforming industries by enabling data-driven decision-making, automation, and predictive analytics. With numerous algorithms available, selecting the right one for a given problem is critical for model accuracy and efficiency. This cheat sheet provides a quick overview of key ML algorithms, helping both beginners and professionals understand their applications, strengths, and limitations. … Read more
Types of Data in Machine Learning
Team Applied AI
Data is the foundation of machine learning, enabling models to learn patterns, make predictions, and improve decision-making. Machine learning algorithms rely on various types of data to perform classification, regression, clustering, and anomaly detection tasks. Understanding different data types is crucial because it affects model accuracy, feature selection, and preprocessing techniques. Some models work best … Read more
Box Plot (Definition, Elements, & Use Cases)
Abhimanyu Saxena
Box plots, also known as box-and-whisker plots, are a fundamental tool in data visualization and statistical analysis. They provide a compact summary of data distribution, helping analysts understand key aspects such as spread, central tendency, and potential outliers in a dataset. One of the biggest advantages of box plots is their ability to visualize data … Read more
10 Real Life Big Data Examples
Big Data refers to the massive and complex datasets generated from various digital sources, including social media, sensors, transactions, and devices. Its significance lies in its potential to drive data-driven decisions, enhance operational efficiency, and foster innovation across industries. In today’s digital world, businesses and organizations leverage big data to uncover hidden patterns, trends, and … Read more
What is AI Bias?
AI bias refers to systematic errors in machine learning models that result in unfair treatment of certain groups or individuals. As AI systems influence critical decisions in healthcare, hiring, and finance, addressing bias is crucial. Unbiased AI promotes fairness, enhances trust, and ensures that technological advancements benefit all members of society equally. What is AI … Read more
Difference between Population and Sample
In research and statistics, population and sample are fundamental concepts used for data collection and analysis. A population refers to the entire group under study, while a sample is a subset of that population selected for analysis. Understanding their differences is crucial because it determines how data is collected and interpreted. Research methods vary depending … Read more