Ambarish-224/Algerian_Forest_Fire_EDA_Practical_Implementation

# Algerian_Forest_Fire_EDA_Practical_Implementation Performing Practical Implementation of EDA and Feature Engineering on Algerian Forest Fire Dataset :- Algerian Forest Fire Dataset Comprises of two regions of Algeria, namely the Bejaia region located in the northeast of Algeria and the Sidi Bel-abbes region located in the northwest of Algeria and Dataset consists of 15 columns and 244 rows. Class Assignment of #FSDSbootcamp @ineuron.ai. Exploratory Data Analysis (EDA) is an approach to analyze the data using visual techniques. It is used to discover trends, patterns, or to check assumptions with the help of statistical summaries and graphical representations. Feature Engineering ( FE ) :- FE is the process of transforming data into features that better represent the underlying problem, resulting in improved Machine Learning Performance. Topic Covered are:- 1) Understanding the Problem Statement. 2) Data Collection 3) Data Cleaning 4) EDA a) Profiling of the Data b) Statistical Analysis c) Graphical Analysis 5) Feature Engineering a) Encoding the Categorical Features b) Handling with Null Values c) Handling with Outlier. Thanks & Regards