Skip to content

Exploratory Data Analysis (EDA) is one of the techniques used for extracting vital features and trends used by machine learning and deep learning models in Data Science

Notifications You must be signed in to change notification settings

EmamulHossen/Exploratory-Data-Analysis-EDA-

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 

Repository files navigation


Machine Learning

Description

Machine learning is an application of AI that enables systems to learn and improve from experience without being explicitly programmed. Machine learning focuses on developing computer programs that can access data and use it to learn for themselves

Features

Features are nothing but the independent variables in machine learning models. What is required to be learned in any specific machine learning problem is a set of these features (independent variables), coefficients of these features, and parameters for coming up with appropriate functions or models (also termed hyperparameters). The following represents a few examples of what can be termed as features of machine learning models:

Screenshots

Tech Used

Pandas NumPy Pandas NumPy

Add More Details:

Anything else that you want to add for users? You can write it here in markdown and see preview in real time. You can add anything that you want, for example

You can add How to Setup:

  • Step 1: this is step 1
  • Step 2: do this, do that

You can add API references

Syntax Description
AndroidX Refactored versions of the Android APIs that are not bundled with the operating system.
AndroidX Test Includes APIs for testing your Android app, including Espresso, JUnit Runner, JUnit4 rules, and UI Automator.

You can add

Links

If you don't want to add this section, just clear all the text written here.

About

Exploratory Data Analysis (EDA) is one of the techniques used for extracting vital features and trends used by machine learning and deep learning models in Data Science

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages