# Linear Regression Analysis | Linear Regression in Python | Machine Learning Algorithms | Simplilearn

August 19, 2024 2024-08-19 7:20# Linear Regression Analysis | Linear Regression in Python | Machine Learning Algorithms | Simplilearn

## Linear Regression Analysis | Linear Regression in Python | Machine Learning Algorithms | Simplilearn

🔥Post Graduate Program In Data Analytics:https://l.linklyhq.com/l/1yhn3

🔥IIT Kanpur Professional Certificate Course In Data Analytics (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Descriptionff&utm_source=youtube

🔥Caltech Data Analytics Bootcamp(US Only): https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Descriptionff&utm_source=youtube

🔥Data Analyst Masters Program (Discount Code – YTBE15): https://www.simplilearn.com/data-analyst-masters-certification-training-course?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Descriptionff&utm_source=youtube

This Linear Regression Analysis video will help you understand the basics of linear regression algorithm. You will learn how Simple Linear Regression works with solved examples, look at the applications of Linear Regression and Multiple Linear Regression model. In the end, we will implement a use case on profit estimation of companies using Linear Regression in Python.

Dataset Link – https://drive.google.com/drive/folders/1BNAsNI6cbwX8I81Wf42xzNtoOzDLw9to

Below topics are covered in this Linear Regression Analysis Tutorial:

1. Introduction to Machine Learning

2. Machine Learning Algorithms

3. Applications of Linear Regression

4. Understanding Linear Regression

5. Multiple Linear Regression

6. Usecase – Profit estimation of companies

What is Linear Regression Analysis?

Machine Learning is an application of Artificial Intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Linear regression is a statistical model used to predict the relationship between independent and dependent variables by examining two factors:

Which variables, in particular, are significant predictors of the outcome variable?

How significant is the regression line in terms of making predictions with the highest possible accuracy?

Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Linear-Regression-NUXdtN1W1FE&utm_medium=Tutorials&utm_source=youtube

To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Linear-Regression-NUXdtN1W1FE&utm_medium=Tutorials&utm_source=youtube

#LinearRegressionAnalysis #LinearRegressionUsingPython #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse #LinearRegressionSimplilearn #simplilearn

➡️ About Caltech Post Graduate Program In Data Science

This Post Graduation in Data Science leverages the superiority of Caltech’s academic eminence. The Data Science program covers critical Data Science topics like Python programming, R programming, Machine Learning, Deep Learning, and Data Visualization tools through an interactive learning model with live sessions by global practitioners and practical labs.

✅ Key Features

– Simplilearn’s JobAssist helps you get noticed by top hiring companies

– Caltech PG program in Data Science completion certificate

– Earn up to 14 CEUs from Caltech CTME

– Masterclasses delivered by distinguished Caltech faculty and IBM experts

– Caltech CTME Circle membership

– Online convocation by Caltech CTME Program Director

– IBM certificates for IBM courses

– Access to hackathons and Ask Me Anything sessions from IBM

– 25+ hands-on projects from the likes of Amazon, Walmart, Uber, and many more

– Seamless access to integrated labs

– Capstone projects in 3 domains

– Simplilearn’s Career Assistance to help you get noticed by top hiring companies

– 8X higher interaction in live online classes by industry experts

✅ Skills Covered

– Exploratory Data Analysis

– Descriptive Statistics

– Inferential Statistics

– Model Building and Fine Tuning

– Supervised and Unsupervised Learning

– Ensemble Learning

– Deep Learning

– Data Visualization

🔥 Advanced Certificate Program In Data Science: https://www.simplilearn.com/pgp-data-science-certification-bootcamp-program?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Descriptionff&utm_source=youtube

For a more detailed understanding of Linear Regression Analysis, do visit: https://bit.ly/2OsDxeA

Learn More at: https://www.simplilearn.com/pgp-data-science-certification-bootcamp-program?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN – 18002127688 / US – +18445327688

source

## Comments (30)

## @SimplilearnOfficial

🔥Post Graduate Program In Data Analytics: https://www.simplilearn.com/pgp-data-analytics-certification-training-course?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Comments&utm_source=youtube

🔥IIT Kanpur Professional Certificate Course In Data Analytics (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-data-analytics?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Comments&utm_source=youtube

🔥Caltech Data Analytics Bootcamp(US Only): https://www.simplilearn.com/data-analytics-bootcamp?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Comments&utm_source=youtube

🔥Data Analyst Masters Program (Discount Code – YTBE15): https://www.simplilearn.com/data-analyst-masters-certification-training-course?utm_campaign=MachineLearning-NUXdtN1W1FE&utm_medium=Comments&utm_source=youtube

## @ariannarisya

Hello. When I did sns.heatmap(companies.corr()), I have error: ValueError: could not convert string to float: 'New York'. I followed all the steps. Thanks

## @user-xb2sl5xp7c

lets paste this

## @jaimeandresgarcia7518

Crystal clear. Thanks.

## @anoushkapalvia7233

Thank you so much for this video and I would like to get the python code used in this tutorial.

## @makulkarni30

Really great course. Can I get the code used in this tutorial.

## @dotdotdotdotdash

one question how does the equation to find M at 11.04 work? I tried to pass it through python but the result is never 0.6

## @francomagalong4860

Hi! May I know how you got 3 in the equation Y=m*X+c; Y=0.6*3+2.2? Thanks.

## @dallasdominguez2224

Fantastic

## @generalideamedia1283

So my question is when doing predictions, are always given a guide (My lecturer calls it a lab) to follow or we have to come with the formats ourselves. Because I believe different predictions come with different times depending on the CSV contents.

## @edgarl.calvadoresii9479

why did u edit only the 3rd row using LabelEncoder?

## @user-iu1jl9ib2m

No way to express my gratitude. Amazing explanation with code. I don't how I missed this video for long time

## @rockfighter9974

Hi Sir /Ma'am,

Why avoided R&D Spend column from model.

I think this is the indipendent variable so why not considering in model. Please explain

## @asimuddin9873

Hello! This video is very helpful to understand the basics of Linear Regression but can you update the code where you import sklearn.preprocessing to transform the State column? Since the latest sklearn library removed categorical_features and hence we are getting errors as "TypeError: __init__() got an unexpected keyword argument 'categorical_features", Thank you!

## @nikhilpatil1894

TypeError: __init__() got an unexpected keyword argument 'categorical_features'

getting this error while executing encoding part. How to solve?

## @tllittle

Superb, thanks

## @033-janardhanpudiparthi3

Provide those csv file

## @olawaleonafeso1597

Loved this so much. Understood the contents perfectly. Thank you

## @robins80

I would like to get access to this dataset.

## @winneronuba8173

I just got to know of simplilearn and good to know it's worth sharing

The detailed explanation is spot on

Can I have the dataset used please?

## @user-ds7jm5rc1x

Thanks for the video! please send me the data file, thanks a lot!!

## @palashislam7510

Can I get the dataset?

## @byronexaporriton318

How could I convert more than one categorical variable to numerical? Thanks!!

## @deniskiplangat127

csv file kindly

## @kondamurirakeshkrishna5178

can u provide us the dataset which ur using in the video

## @maxmacken8859

Great video! can i get the csv file thanks

## @DidaKusAlex

Hi, i have to say Amazing video, I had seen a lot of videos looking for a easy way to learn, but this video is the best, I can get it! I think you should update the code because the part "categorical_features" doesn't work.

thanks for shared this information and learn us about ML.

## @sebastianfarias5670

Thank you soooo much for such an amazing video on linear regression, +1 sub !!!!!

## @natashasamuel9346

Great class.

Keep up the good work.

Thank You,

Natasha Samuel

## @merhaiakshay9625

is it possible to get the powerpoint presentation? please