WebAug 3, 2024 · We will load the titanic dataset into python to perform EDA. #Load the required libraries import pandas as pd import numpy as np import seaborn as sns #Load the data df = pd.read_csv('titanic.csv') #View the data df.head() Our data is ready to be explored! 1. Basic information about data - EDA WebMar 31, 2024 · Titanic Dataset Analysis is a popular classification dataset for beginners. It is a Kaggle project which uses machine learning to predict the survival of passengers in the titanic. The objective of this project is to submit the prediction result with the best accuracy.
GitHub - josefelbez/TitanicAnalysis: Titanic Analysis
WebEDA of Titanic dataset with Python (Analysis) Kaggle. Jamil Moughal · 5y ago · 17,168 views. arrow_drop_up. Copy & Edit. Web5 hours ago · Handling outliers is an important task in data analysis, as they can significantly affect statistical measures and machine learning models. In this tutorial, we will learn how to handle outliers in Python Pandas. We will cover the following topics: ... Implementing Decision Tree Algorithm for Classification with Titanic Dataset in Python. mobile phone with sim offers usa
titanic - datasets CatBoost
WebSep 5, 2024 · This is my take on machine learning for the iconic Titanic ML dataset. Purpose is not in accuracy of predictions, but rather as a refresher to the different data analysis technique and to the different ML techniques. Will come back from time to time to refresh the techniques used as I become more familiar with data science and machine learning! WebIn this blog post, we will explore how to use the Python Pandas library to analyze large datasets. We will be using the Titanic dataset, a well-known dataset that contains information about the passengers on the Titanic ship that sank in 1912. The Pandas library is a powerful tool for data manipulation and analysis. It provides a data structure ... WebAug 10, 2024 · The dataset consists of the information about people boarding the famous RMS Titanic. Various variables present in the dataset includes data of age, sex, fare, ticket etc. The dataset comprises of 891 observations of 12 columns. Below is a table showing names of all the columns and their description. Importing packages mobile phone with sd card slot