Introduction to Pandas Library – Interactive Cares

Lesson List

Prerequisites for Data Science

Introduction to Pandas Library00:14:43

Undestanding DataFrame and Series00:10:03

Customizing DataFrame and Series00:19:35

Manipulating DataFrame and Series00:10:26

Pandas Quiz

Understanding Array in Numpy00:6:29

Statistical methods Concepts00:09:50

Statistical methods (T-test, P-value)00:12:06

Statistical methods in Python00:08:51

Conditional Probability00:13:30

Playing with Conditional Probability00:10:16

Univariate, Bi-variate hypothesis testing (Part 1)00:12:22

Univariate, Bi-variate hypothesis testing (Part 2)00:13:25

Numpy Quiz

Data Visualization with matplotlib

Introduction to matplotlib Library00:13:57

Histogram and Scatter plot00:12:33

Stack plot and Pie chart00:17:05

Importing Live Data into graph00:16:04

Customizing labels, grid, axis and color00:10:9

Matplotlib style and customization00:14:02

Creating sub-plots (Part 1)00:09:24

Creating sub-plots (Part 2)00:10:44

Creating 3D plots00:16:39

Matplotlib Quiz

Regression and Naïve Bayes Algorithm

Bayesian Theorem and Linear Regression00:13:27

Linear Regression Program (Part 1)00:08:41

Polynomial Regression and Multivariate Regression00:7:20

Polynomial Regression Program00:14:05

Multivariate Regression: Ordinary Least Square Method00:16:07

Naïve Bayes Algorithm concept00:11:27

Naïve Bayes Algorithm (Part 1)00:11:43

Naïve Bayes Algorithm (Part 2)00:15:52

Linear Regression Program (Part 2)00:11:03

Regression Quiz

Machine Learning Models

Introduction to Machine learning (Part 1)00:14:56

Introduction to Machine learning (Part 2)00:9:40

Supervised and Unsupervised Learning concept00:12:00

Train and Test data (Part 1)00:15:48

Train and Test data (Part 2)00:8:55

K-Means Clustering and Cross Validation Concept00:7:35

K-Means Clustering program00:20:00

Decision Tree Concept00:13:15

Ensemble Learning and Support Vector Machine Concept00:08:04

Decision Tree Spam Classifier (Part 1)00:18:57

Decision Tree Spam Classifier (Part 2)00:11:07

Decision Tree Spam Classifier (Part 3)00:13:49

K-nearest Neighbor (KNN) and K-fold Cross Validation Concept00:09:35

Using KNN to predict movie ratings (Part 1)00:13:25

Using KNN to predict movie ratings (Part 2)00:18:54

Using KNN to predict movie ratings (Part 3)00:12:34

K-Fold Cross validation (Model performance evaluation)00:14:00

Machine Learning Quiz

Bonous Project

Introduction to Pandas Library

Attachments

d.csv 2.39 MB

Android App Development

AR-VR

ArcGIS

AUTOCAD

BCS

Big Data and Machine Learning

Case Solving

Complete Career Path

Content Marketing

CV Writing

Cyber Security

Data Analytics

Data Structure & Algorithm

Django

English Grammar

Entrepreneurship

Free Course

Graphic Design

GRE

IBA-MBA

Find your desired course

Select Your Favourite Category And Start Learning.

Android App Development

AR-VR

ArcGIS

AUTOCAD

BCS

Big Data and Machine Learning

Case Solving

Complete Career Path

Content Marketing

CV Writing

Cyber Security

Data Analytics

Data Structure & Algorithm

Django

English Grammar

Entrepreneurship

Free Course

Graphic Design

GRE

IBA-MBA

Prerequisites for Data Science

Introduction to Pandas Library00:14:43

Undestanding DataFrame and Series00:10:03

Customizing DataFrame and Series00:19:35

Manipulating DataFrame and Series00:10:26

Pandas Quiz

Understanding Array in Numpy00:6:29

Statistical methods Concepts00:09:50

Statistical methods (T-test, P-value)00:12:06

Statistical methods in Python00:08:51

Conditional Probability00:13:30

Playing with Conditional Probability00:10:16

Univariate, Bi-variate hypothesis testing (Part 1)00:12:22

Univariate, Bi-variate hypothesis testing (Part 2)00:13:25

Numpy Quiz

Data Visualization with matplotlib

Introduction to matplotlib Library00:13:57

Histogram and Scatter plot00:12:33

Stack plot and Pie chart00:17:05

Importing Live Data into graph00:16:04

Customizing labels, grid, axis and color00:10:9

Matplotlib style and customization00:14:02

Creating sub-plots (Part 1)00:09:24

Creating sub-plots (Part 2)00:10:44

Creating 3D plots00:16:39

Matplotlib Quiz

Regression and Naïve Bayes Algorithm

Bayesian Theorem and Linear Regression00:13:27

Linear Regression Program (Part 1)00:08:41

Polynomial Regression and Multivariate Regression00:7:20

Polynomial Regression Program00:14:05

Multivariate Regression: Ordinary Least Square Method00:16:07

Naïve Bayes Algorithm concept00:11:27

Naïve Bayes Algorithm (Part 1)00:11:43

Naïve Bayes Algorithm (Part 2)00:15:52

Linear Regression Program (Part 2)00:11:03

Regression Quiz

Machine Learning Models

Select Your Favourite
Category And Start Learning.