Skip to content

Latest commit

 

History

History
48 lines (36 loc) · 2.03 KB

README.md

File metadata and controls

48 lines (36 loc) · 2.03 KB
Raw

Data Visualization

You can find more information about our Data Visualization Course by visiting Course Website

In the age of Artificial Intelligence, understanding, interpreting and analyzing data has become one of the most important competencies. Being able to make sense of the incredible variety of data around us is a part of our new life dynamics. Conventional methods are insufficient to make sense of high volume data, which is called "Big Data". "Data Visualization", which emerged to facilitate the statistical inferences of the human brain about data by visualizing the data, surpasses other methods in this regard.

Data visualization greatly helps a data scientist to determine in advance whether the created artificial intelligence model will perform as expected and whether the data is suitable for the problem. One of the main reasons for this is that visualizations of complex distributions and algorithms can be interpreted more easily and effectively than numerical statistical outputs. One of the most important aspects of data visualization is that it provides the fastest interpretation and transmission of data-related information in a universal way by using visual information.

List of Contents

Prologue

  • Welcome to Data Visualization Course
  • What Is Visualization?
  • Why Do We Need Visualization?
  • The Importance of Visualization In Data Science World

Introduction to Data

  • What is Data
  • What is Data Visualization?
  • Advantages of Data Visualization
  • Data Types

Installations ve Datasets

  • Libraries
  • Datasets

Visualizations Types

  • Bar Chart, Histogram, Box Plot
  • Line Chart, Pie Chart
  • Scatter Plot, Heatmap

End-to-end Applied Data Visualization Project

  • Titanic Dataset
  • Exploratory Data Analysis
  • Data Preprocessing
  • Defining Data Visualization Types
  • Creating Report

Epilogue

  • Practical Use Of What Has Been Learned
  • Further Projects
  • What’s Next?