Категории

Getting our data ready - Filling in missing values - Part 1 - 34

Опубликовано: 09 Август 2026
на канале: IT Guys
43
1

Today we will be doing the third step of getting our data ready: filling in missing values in our dataset. This is an important step since machine learning models can't predict with missing values. In this part we will be learning to do this with the Pandas Library.


Here is the dataset I used:
https://github.com/sush3011/MachineLe...


#Scikit-learn #MachineLearning #MachineLearningModels #Pandas #Python #ML

play_arrow
14
1

Deadlock in Operating System

Deadlock in Operating System
play_arrow
20
0

Waffle Play's Unturned - Surviving On The Tutorial World - Part 2

Waffle Play's Unturned - Surviving On The Tutorial World - Part 2
play_arrow
428
6

Moving Car & Walking Man Project in C/C++ Small project

Moving Car & Walking Man Project in C/C++ Small project
play_arrow
51,956
117

free download

free download
play_arrow
31,244
116

X-ACTO® KS™ Manual Classroom Pencil Sharpener (1031)

X-ACTO® KS™ Manual Classroom Pencil Sharpener (1031)
play_arrow
3,849
42

All rewards from Fatal season 26 Mad fut 21

All rewards from Fatal season 26 Mad fut 21
play_arrow
7,552
48

CaptchaApp - МАШЕННИЧЕСТВО.

CaptchaApp - МАШЕННИЧЕСТВО.
play_arrow
17
2

ariana mashup edit

ariana mashup edit
Похожие видео
play_arrow
Evaluating a machine learning model - Scikit-Learn evaluation functions - 51

Evaluating a machine learning model - Scikit-Learn evaluation functions - 51
play_arrow
Evaluiating a machine leaning model - FINALLY using the scoring Paramter - 50

Evaluiating a machine leaning model - FINALLY using the scoring Paramter - 50
play_arrow
Regression model evaluation metrics - Part 2(Mean squared error) - 49

Regression model evaluation metrics - Part 2(Mean squared error) - 49
play_arrow
Regression model evaluation metrics - Part 2(Mean absolute error) - 48

Regression model evaluation metrics - Part 2(Mean absolute error) - 48
play_arrow
Regression model evaluation metrics - Part 1(R^2) - 47

Regression model evaluation metrics - Part 1(R^2) - 47
play_arrow
Evaluating a classification model with evaluation metrics - Part 4(Classsification Report) - 46

Evaluating a classification model with evaluation metrics - Part 4(Classsification Report) - 46
play_arrow
Evaluating a classification model with evaluation metrics - Part 3(Confusion Matrix) - 45

Evaluating a classification model with evaluation metrics - Part 3(Confusion Matrix) - 45
play_arrow
Evaluating a Classification model with evaluation metrics - Part 2(Area under ROC curve) - 44

Evaluating a Classification model with evaluation metrics - Part 2(Area under ROC curve) - 44
play_arrow
Evaluating a Classification model with evaluating metrics - Part 1(Accuracy) - 43

Evaluating a Classification model with evaluating metrics - Part 1(Accuracy) - 43
play_arrow
Evaluating a machine learning model - Part 2 - 42

Evaluating a machine learning model - Part 2 - 42
play_arrow
Evaluating a machine learning model - Part 1 - 41

Evaluating a machine learning model - Part 1 - 41
play_arrow
Making predictions with a machine learning model - Part 2 - 40

Making predictions with a machine learning model - Part 2 - 40
play_arrow
Making predictions with machine learning models - Part 1 - 39

Making predictions with machine learning models - Part 1 - 39
play_arrow
Fitting a machine learning model - 38

Fitting a machine learning model - 38
play_arrow
Choosing the right machine-learning model with scikit-learn - Part 2 - 37

Choosing the right machine-learning model with scikit-learn - Part 2 - 37
play_arrow
Choosing the right Machine Learning Model with Scikit-Learn - Part 1 - 36

Choosing the right Machine Learning Model with Scikit-Learn - Part 1 - 36
play_arrow
Getting our data ready - Filling in missing values - Part 2 - 35

Getting our data ready - Filling in missing values - Part 2 - 35
play_arrow
Getting our data ready - Filling in missing values - Part 1 - 34

Getting our data ready - Filling in missing values - Part 1 - 34
play_arrow
Getting our data ready - Converting non-numerical values into numerical values - 33

Getting our data ready - Converting non-numerical values into numerical values - 33
play_arrow
Getting our data ready - Splitting our data - 32

Getting our data ready - Splitting our data - 32
play_arrow
A typical Scikit-Learn workflow - 31

A typical Scikit-Learn workflow - 31
play_arrow
Introduction to Scikit-Learn - 30

Introduction to Scikit-Learn - 30
play_arrow
Matplotlib project - 29

Matplotlib project - 29
play_arrow
Customising and styling Matplotlib plots - 28

Customising and styling Matplotlib plots - 28