Introduction Imagine trying to understand what someone said over a noisy phone call or deciphering a DNA sequence from partial biological data. In both cases, you're trying to uncover a hidden...
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Introduction Imagine trying to understand what someone said over a noisy phone call or deciphering a DNA sequence from partial biological data. In both cases, you're trying to uncover a hidden...
Imagine teaching a robot to navigate a maze or training an AI to master a video game without ever giving it explicit instructions—only rewarding it when it does something right. This is the essence...
What is Data Filtering? Data filtering is sifting through a dataset to extract the specific information that meets certain criteria while excluding irrelevant or unwanted data. It's a foundational...
What is Data Encoding? Data encoding is the process of converting data from one form to another to efficiently store, transmit, and interpret it by machines or systems. Think of it like translating...
What Is Data Wrangling? Data is the foundation of modern decision-making, but raw data is rarely clean, structured, or ready for analysis. This is where data wrangling comes in. Also known as data...
What is Z-Score Normalization? Z-score normalization, or standardization, is a statistical technique that transforms data to follow a standard normal distribution. This process ensures that data has...
What is Elastic Net Regression? Elastic Net regression is a statistical and machine learning technique that combines the strengths of Ridge (L2) and Lasso (L1) regularisation to improve predictive...
What is Recursive Feature Elimination? In machine learning, data often holds the key to unlocking powerful insights. However, not all data is created equal. Some features in a dataset contribute...
What is High-Dimensional Data? High-dimensional data refers to datasets that contain a large number of features or variables relative to the number of observations or samples. In other words, each...
Introduction Text data is everywhere—from social media posts and customer reviews to emails and product descriptions. For data scientists and analysts, working with this unstructured form of data...
What is Missing Data in Machine Learning? In machine learning, the quality and completeness of data are often just as important as the algorithms and models we choose. Though common in real-world...
What is Predictive Analytics? Predictive analytics uses historical data, statistical algorithms, and machine learning techniques to identify patterns and forecast future outcomes. At its core, it...
What is Linear Regression in Machine Learning? Linear regression is one of the fundamental techniques in machine learning and statistics used to understand the relationship between one or more...
What is a Confusion Matrix? A confusion matrix is a fundamental tool used in machine learning and statistics to evaluate the performance of a classification model. At its core, a tablet lets you...
What is Ordinary Least Squares (OLS)? Ordinary Least Squares (OLS) is a fundamental technique in statistics and econometrics used to estimate the parameters of a linear regression model. In simple...
What is the METEOR Score? The METEOR score, which stands for Metric for Evaluation of Translation with Explicit ORdering, is a metric designed to evaluate the text quality generated by machine...
What is BERTScore? BERTScore is an innovative evaluation metric in natural language processing (NLP) that leverages the power of BERT (Bidirectional Encoder Representations from Transformers) to...
What is the BLEU Score in NLP? BLEU, Bilingual Evaluation Understudy, is a metric used to evaluate the quality of machine-generated text in NLP, most commonly in machine translation. Kishore...
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