Exploratory Data Analysis (EDA) | Understand Data Before Modeling | MRU E-Learning
Exploratory Data Analysis (EDA) is a crucial step in the data science workflow that helps uncover patterns, trends, and anomalies in data.
In this MRU E-Learning session, learn how to analyze, visualize, and summarize datasets to gain meaningful insights before applying machine learning models.
This video is ideal for students and beginners in Data Science, Machine Learning, and Analytics.
📘 Topics Covered:
✔️ What is Exploratory Data Analysis (EDA)?
✔️ Importance of EDA in Data Science
✔️ Types of Data & Variables
✔️ Descriptive Statistics
✔️ Data Cleaning & Handling Missing Values
✔️ Univariate & Multivariate Analysis
✔️ Data Visualization Techniques
✔️ Outlier Detection
✔️ Insights from EDA
exploratory data analysis
EDA tutorial
data analysis basics
data visualization
data preprocessing
EDA for machine learning
statistics for data science
data cleaning
MRU E-Learning
data analytics fundamentals
EDA techniques
#ExploratoryDataAnalysis #EDA #DataScience
#DataAnalytics #MachineLearning
#MRUElearning #TechEducation #DataVisualization
#Analytics #LearnDataScience