Utilize this oppurtunity , QnA section !!

How to follow this course-must watch

How to install Anaconda & Jupyter Notebook

Intro !!

Quick Summary of Jupyter Notebook

Introduction to Problem Statement

Understand the big Idea- how to collect data !

How to Automate your code !

Perform descriptive analysis on Data !

Perform Exploratory Data Analysis to understand Patterns

Analyse whether Google is Bias or not !

Analysing distrbution of Ratings

Automate your data Visualisation code ..

Understand Hidden patterns from data..

Perform Data Preparation for Analysing App Category

Analysing Android version of data

Lets Perform Data Cleaning..

Lets Clean & ready our Rating & Installs feature

Perform Feature Selection algorithms to select important features

How Feature selection works..

What are outliers & how to find it..

Perform Data-Preparation on Size Feature..

Outliers Detection using IQR..

How to Impute Outliers

Outlier Detection in Install feature

what is Data Transformation

What are Missing Values & how to fill Missing values

What is Data Discretization & how to apply it in real-world

What is Mean Encoding & how to apply it in real world

What is Target Guided Mean Encoding

Intuition behind Logistic Regression-part 2

Intuition behind Logistic Regression-part 1

Applying Label Encoding & preparing your data for Data Modelling

What is Label Encoding & how to apply it in real-world

Intuition Behind Decision Trees - Part 1

Intuition Behind Decision Trees - Part 2

Intuition Behind Decision Trees - Part 3

Building Logistic Regression Model

Intuition Behind Decision Trees - Part 5

Intuition Behind Decision Trees - Part 4

Intuition Behind Decision Trees - Part 6

Intuition Behind Random Forest - Part 2

Intuition Behind Random Forest - Part 1

Hypertune your Logistic Regression Model

Hypertune your Random Forest Model

How to load data & fill missing values in data !

Fix Missing values of Data !

How to fill Missing values using Random Value Imputation

Perform Wordcloud Analysis

Lets Clean Description Feature

Perform Unigram , bigram & trigram analysis..

Perform GeoSpatial Analysis

Lets Prepare Description Feature using nltk !

Obtaining label distribution of data

Imputing the outliers..

how to visualize outliers..

Perform In-depth analysis on data

Extract important features using Co-relation..

Lets pre-process our data for Feature Encoding..

Automate your Data Preparation stuffs !

What is Frequency Encoding & how to apply it in Real-World

Lets Build a Decision Tree Model

Playing with Multiple Algorithms..

Lets Hypertune our model..

Lets Prepare our Data..

Finding co-relation values of a matrix..

Define own function to understand our Data !

Perform In-Depth Analysis !

Finding relationship in data !

Data Preparation for Modelling !

Build a Machine learning Model..

Lets explore our data !