Titanic Dataset EDA (Titanic Survival Predictor) | Part 1

Описание: Welcome to EDA Journey: Day by Day
📂 In This Video:
We’ll perform Exploratory Data Analysis (EDA) on the famous Titanic Dataset.
EDA is one of the most important steps in any data science or machine learning project. It helps you understand patterns, detect missing values, spot outliers, and gain insights before building predictive models.

Using Python libraries like Pandas, Matplotlib, and Seaborn, we’ll analyze the Titanic dataset step by step to uncover hidden insights about survival.

🧠 What You’ll Learn in This Video:

What EDA is and why it’s important

How to analyze Titanic dataset with Python

Handling missing values & data cleaning

Visualizations to explore survival patterns

Insights for building ML models

⏳ Timestamps:
00:00 – Introduction to EDA
04:00 – Making Virtual Environment
08:59 – Step 1: Understanding Data
09:12 – Checking Missing Values
09:38 – Checking Duplicate Values
10:06 – Checking Number of Unique values in Column
11:36 – Checking Info
11:59 – Using Describe Function
18:00 – Separating columns according to data type
20:25 – Checking Target Variables
22:28 – Analysis (Univariate & Multi-Variate)
22:13 – Analysis on Categorical columns
32:42 – Analysis on Numerical columns

This skill is essential for data preprocessing and will make your machine learning projects stronger and more reliable.

📂 This video is part of my playlist:
👉 ML Journey: Day by Day

🔗 Source Code on GitHub:


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#TitanicDataset #EDA #ExploratoryDataAnalysis #MachineLearning #DataScience #Python #Seaborn #Pandas #Matplotlib #MLTutorial #DataAnalysis #MLJourney