Visualizing Anomalies in the Dataset
Visualizing Anomalies in the Dataset
with security_ninja|4 years experience
116638total views
Session 1 Intro and Setting up Project Environment
Aug 3, 2020 | 6:53 PM3:57
Session 2.2 Using different format strings and Styles in Matplotlib Plots
Aug 3, 2020 | 6:55 PM17:18
Session 2.3 Create Subplots and Plotting Vertical Bar plots
Aug 3, 2020 | 6:55 PM15:17
Session 2.4 Plotting Pie Charts using Matplotlib Library
Aug 3, 2020 | 6:55 PM15:3
Session 2.5 Plotting Stack Plots and Area Plots using Matplotlib Library
Aug 3, 2020 | 6:55 PM10:48
Session 2.6 Plotting Histograms using Matplotlib Library
Aug 3, 2020 | 6:55 PM13:13
Session 3.1 Pandas dataframe visualization using Matplotlib Library
Aug 3, 2020 | 6:55 PM11:22
Session 3.2 Plotting Numerical and Categorical variables of pandas dataframe using Matplotlib Library
Aug 3, 2020 | 6:55 PM12:29
Session 3.3 How to fill Missing Numerical values in the Pandas Dataframes
Aug 3, 2020 | 6:55 PM16:27
Session 3.4 How to fill Missing Categorical values in the Pandas Dataframes
Aug 3, 2020 | 6:55 PM10:55
Session 4.1 Data Visualization using Seaborn Library Part 1
Aug 3, 2020 | 6:55 PM10:
Session 4.2 Data Visualization using Seaborn Library Part 2
Aug 3, 2020 | 6:55 PM13:45
Session 4.3 Data Visualization using Seaborn Library Part 3
Aug 3, 2020 | 6:56 PM11:53
Session 5.1 Case Study - Classify Personal Income
Aug 3, 2020 | 6:56 PM19:15
Session 5.2 Classifying Personal Income and Doing Bivariate analysis
Aug 3, 2020 | 6:56 PM9:44
Session 5.3 Using Logistic Regression Model
Aug 3, 2020 | 6:56 PM11:16
Session 5.4 Validating Model accuracy and confusion
Aug 3, 2020 | 6:56 PM8:19
Session 5.5 Removing Insignificant Variables and Building KNN classfier
Aug 3, 2020 | 6:56 PM13:22
Session 5.6 Improving KNN Model Accuraccy and Intro to Case Etudy 2
Aug 3, 2020 | 6:56 PM6:6
Session 2.1 How to Install Matplotlib library and Draw your First Plot
Aug 13, 2020 | 6:55 PM9:11
Visualizing Anomalies in the Dataset
- English
- Data Science
Data Visualization- Project length: 4h 00m
In this project, we will learn how to visualize data using different python visualization libraries such as Matplotlib and Seaborn. We will also look at how to extract, clean, transform and load the data from different files into Dataframes.
Overview
Introduction
In this project, we will learn how to visualize data using different python visualization libraries such as Matplotlib and Seaborn. We will also look at how to extract, clean, transform, and load the data from different files into Dataframes. Dataframes are special data structures used specifically for storing data and helps us to visualize it. You will also learn how to use the Pandas library along with Matplotlib and Seaborn to create stunning dashboards. You will learn How to plot different types of Plots, Charts, Graphs, and also customize them as per your requirements. While learning Data Science it's always the best thing to solve case studies in order to grasp the concepts more effectively.
What are the requirements?
- Basic knowledge of Python Programming Knowledge.
- Basic knowledge of how to use Integrated Programming Environment (IDE)
What is the target audience?
- Anyone want to learn how to Visualize Anomalies in the Dataset
- Anyone who is interested in Learning how to leverage different libraries for Data Visualization
- Anyone who is willing to learn the cutting edge technologies.
Project Outline
The project outline explains what you will learn in each session
In this video, I will show you What are the requirements and how to setup Project Environment.