KE
Uploaded byKirill Eremenko
PPTX, PDF4,450 views

Deep Learning A-Z™: Regression & Classification - Simple Linear Regression - Step 1

Simple linear regression is a technique for modeling the relationship between a dependent variable (y) and a single independent variable (x) using an equation of y = b0 + b1*x. The dependent variable is represented on the y-axis and the independent variable on the x-axis, with the goal of finding the best fit linear relationship between the two.

Education◦
Related topics:
Deep Learning•

Embed presentation

Downloaded 174 times
© SuperDataScienceDeep Learning A-Z
© SuperDataScienceDeep Learning A-Z Simple Linear Regression y = b0 + b1*x1 Dependent variable (DV) Independent variable (IV) CoefficientConstant
© SuperDataScienceDeep Learning A-Z Simple Linear Regression: Salary ($) Experience y = b0 + b1*x Salary = b0 + b1 *Experience +1yr +10k 30k

More Related Content

PPTX
Deep Learning A-Z™: Regression & Classification - Module 7
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - Module 4
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - Module 3
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Regression & Classification - Logistic Regression
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machine - Module 5 - Boltzmann Machine
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Module 5
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Neuron
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - The Vanishing Gradient ...
byKirill Eremenko
 
Deep Learning A-Z™: Regression & Classification - Module 7
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - Module 4
byKirill Eremenko
 
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - Module 3
byKirill Eremenko
 
Deep Learning A-Z™: Regression & Classification - Logistic Regression
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machine - Module 5 - Boltzmann Machine
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Module 5
byKirill Eremenko
 
Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Neuron
byKirill Eremenko
 
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - The Vanishing Gradient ...
byKirill Eremenko
 

What's hot

PPTX
Deep Learning A-Z™: Regression - Multiple Linear Regression Intuition
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - Practical Intuition
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Regression & Classification - Simple Linear Regression - ...
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Artificial Neural Networks (ANN) - Backpropagation
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Artificial Neural Networks (ANN) - How do Neural Networks...
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Artificial Neural Networks (ANN) - Module 1
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - The Idea Behind Recurre...
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 1)
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - LSTMs
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Contrastive Divergence
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Activation Function
byKirill Eremenko
 
PDF
パターン認識第9章 学習ベクトル量子化
byMiyoshi Yuya
 
PDF
[DL輪読会]Disentangling by Factorising
byDeep Learning JP
 
PDF
Re永続データ構造が分からない人のためのスライド
byMasaki Hara
 
PDF
初めてのグラフカット
byTsubasa Hirakawa
 
PDF
モンテカルロサンプリング
byKosei ABE
 
PPTX
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 1(b): ReLU Layer
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Summary
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Module 2
byKirill Eremenko
 
PDF
目指せグラフマスター
byHCPC: 北海道大学競技プログラミングサークル
 
Deep Learning A-Z™: Regression - Multiple Linear Regression Intuition
byKirill Eremenko
 
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - Practical Intuition
byKirill Eremenko
 
Deep Learning A-Z™: Regression & Classification - Simple Linear Regression - ...
byKirill Eremenko
 
Deep Learning A-Z™: Artificial Neural Networks (ANN) - Backpropagation
byKirill Eremenko
 
Deep Learning A-Z™: Artificial Neural Networks (ANN) - How do Neural Networks...
byKirill Eremenko
 
Deep Learning A-Z™: Artificial Neural Networks (ANN) - Module 1
byKirill Eremenko
 
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - The Idea Behind Recurre...
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 1)
byKirill Eremenko
 
Deep Learning A-Z™: Recurrent Neural Networks (RNN) - LSTMs
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Contrastive Divergence
byKirill Eremenko
 
Deep Learning A-Z™: Artificial Neural Networks (ANN) - The Activation Function
byKirill Eremenko
 
パターン認識第9章 学習ベクトル量子化
byMiyoshi Yuya
 
[DL輪読会]Disentangling by Factorising
byDeep Learning JP
 
Re永続データ構造が分からない人のためのスライド
byMasaki Hara
 
初めてのグラフカット
byTsubasa Hirakawa
 
モンテカルロサンプリング
byKosei ABE
 
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 1(b): ReLU Layer
byKirill Eremenko
 
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Summary
byKirill Eremenko
 
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Module 2
byKirill Eremenko
 
目指せグラフマスター
byHCPC: 北海道大学競技プログラミングサークル
 

More from Kirill Eremenko

PPTX
Deep Learning A-Z™: Autoencoders - Sparse Autoencoders
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Autoencoders - Contractive Autoencoders
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Autoencoders - Stacked Autoencoders
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Autoencoders - Denoising Autoencoders
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Restricted Boltzmann Machine
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Deep Belief Networks
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Energy Based Models (ebm)
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: AutoEncoders - Training an AutoEncoder
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: AutoEncoders - Module 6
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Deep Boltzmann Machines
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Boltzmann Machine
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: AutoEncoders - AutoEncoders
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Boltzmann Machines - Plan of Attack
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 2)
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - Reading an Advanced SOM
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - K-Means Clustering (part 2)
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Self Organizing Maps (SOM) - K-Means Clustering
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 1: Convolution...
byKirill Eremenko
 
PPTX
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 3: Flattening
byKirill Eremenko
 
Deep Learning A-Z™: Autoencoders - Sparse Autoencoders
byKirill Eremenko
 
Deep Learning A-Z™: Autoencoders - Contractive Autoencoders
byKirill Eremenko
 
Deep Learning A-Z™: Autoencoders - Stacked Autoencoders
byKirill Eremenko
 
Deep Learning A-Z™: Autoencoders - Denoising Autoencoders
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Restricted Boltzmann Machine
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Deep Belief Networks
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Energy Based Models (ebm)
byKirill Eremenko
 
Deep Learning A-Z™: AutoEncoders - Training an AutoEncoder
byKirill Eremenko
 
Deep Learning A-Z™: AutoEncoders - Module 6
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Deep Boltzmann Machines
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Boltzmann Machine
byKirill Eremenko
 
Deep Learning A-Z™: AutoEncoders - AutoEncoders
byKirill Eremenko
 
Deep Learning A-Z™: Boltzmann Machines - Plan of Attack
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - How do SOMs learn (part 2)
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - Reading an Advanced SOM
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - K-Means Clustering (part 2)
byKirill Eremenko
 
Deep Learning A-Z™: Self Organizing Maps (SOM) - K-Means Clustering
byKirill Eremenko
 
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 1: Convolution...
byKirill Eremenko
 
Deep Learning A-Z™: Convolutional Neural Networks (CNN) - Step 3: Flattening
byKirill Eremenko
 

Recently uploaded

PPTX
LYMPHATIC SYSTEM.pptx it includes lymph, lymph nodes, bone marrow, spleen
byReena Yadav
 
PPTX
Time Series Analysis - Method of Simple Moving Average 3 Year and 4 Year Movi...
bySundar B N
 
PPTX
SEMESTER 5 UNIT- 1 Difference of Children and adults.pptx
bysachin7989
 
PPTX
How to create a Pass-Fail quality check in Odoo 18 Quality
byCeline George
 
PPTX
Psychological disorders affecting students well being.pptx
bymunushah
 
PPTX
Quarter 3 lesson 2 of English Grade 8.pptx
byMamGamino
 
PPTX
Plant Breeding: Its History and Contribution
bySatyam Sharma
 
PPTX
An Complete Overview of Chatter in Odoo 18
byCeline George
 
PDF
Past Memories and a New World: Photographs of Stoke Newington from the 70s, 8...
byHistory of Stoke Newington
 
PDF
“Step-by-Step Fabrication of Bipolar Junction Transistors (BJTs)”
byGS Virdi
 
PPTX
ATTENTION - PART 1.pptx cognitive processes -For B.Sc I Sem By Mrs.Shilpa Hot...
bySHILPA HOTAKAR
 
PPTX
A Presentation of PMES 2025-2028 with Salient features.pptx
byRoyPintor2
 
PDF
UGC NET Paper 1 Syllabus | 10 Units Complete Guide for NTA JRF
byNIKHIL K N
 
PPTX
How to Create & Configure Web Controllers in Odoo 18
byCeline George
 
PPTX
Time Series Analysis - Weighted (Unequal) Moving Average Method
bySundar B N
 
PPTX
Comprehensive Lecture on Power Supply Design: Rectifiers and Voltage Regulators
byGS Virdi
 
PPTX
Declaration of Helsinki Basic principles in medical research ppt.pptx
byRanikonde
 
PPTX
Appreciations - Nov 25.pptxjkjjkjjkjejfkejfkjekjekjkjekjekjkjekjktejektj
bypreetheshparmar
 
PDF
LH_Lecture Note on Spices , AI And Importance in Human Life.pdf
bybisensharad
 
PDF
DEFINITION OF COMMUNITY Sociology. .pdf
byJhasketan Kuanar
 
LYMPHATIC SYSTEM.pptx it includes lymph, lymph nodes, bone marrow, spleen
byReena Yadav
 
Time Series Analysis - Method of Simple Moving Average 3 Year and 4 Year Movi...
bySundar B N
 
SEMESTER 5 UNIT- 1 Difference of Children and adults.pptx
bysachin7989
 
How to create a Pass-Fail quality check in Odoo 18 Quality
byCeline George
 
Psychological disorders affecting students well being.pptx
bymunushah
 
Quarter 3 lesson 2 of English Grade 8.pptx
byMamGamino
 
Plant Breeding: Its History and Contribution
bySatyam Sharma
 
An Complete Overview of Chatter in Odoo 18
byCeline George
 
Past Memories and a New World: Photographs of Stoke Newington from the 70s, 8...
byHistory of Stoke Newington
 
“Step-by-Step Fabrication of Bipolar Junction Transistors (BJTs)”
byGS Virdi
 
ATTENTION - PART 1.pptx cognitive processes -For B.Sc I Sem By Mrs.Shilpa Hot...
bySHILPA HOTAKAR
 
A Presentation of PMES 2025-2028 with Salient features.pptx
byRoyPintor2
 
UGC NET Paper 1 Syllabus | 10 Units Complete Guide for NTA JRF
byNIKHIL K N
 
How to Create & Configure Web Controllers in Odoo 18
byCeline George
 
Time Series Analysis - Weighted (Unequal) Moving Average Method
bySundar B N
 
Comprehensive Lecture on Power Supply Design: Rectifiers and Voltage Regulators
byGS Virdi
 
Declaration of Helsinki Basic principles in medical research ppt.pptx
byRanikonde
 
Appreciations - Nov 25.pptxjkjjkjjkjejfkejfkjekjekjkjekjekjkjekjktejektj
bypreetheshparmar
 
LH_Lecture Note on Spices , AI And Importance in Human Life.pdf
bybisensharad
 
DEFINITION OF COMMUNITY Sociology. .pdf
byJhasketan Kuanar
 

Deep Learning A-Z™: Regression & Classification - Simple Linear Regression - Step 1