Simple Linear Regression | Mathematical Formulation | Coding from Scratch

In this video, we break down the formula and guide you through coding from scratch in Python. Watch, learn, and build a solid understanding of this foundational regression technique.
Code used: github.com/campusx-official/1...
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⌚Time Stamps⌚
00:00 - Intro
01:15 - Revision / How to Find 'm' and 'b'
40:06 - Coding from Scratch
53:10 - Outro

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You deserve more respect bro....really i admire you...No one give interpretation and inferences like u. And please make a videos on Neural Network and NLP.

[@akash.deblanq]

Finally in model. Your explanation is clearer for me compared to even Andrew Ng. I am not kidding. Thank you Nitish. :)

[@tusharsub1000]

Yes, I too feel the same...

[@iamsomeone54]

real

[@arghadeepmisra7865]

@@iamsomeone54 I came here just because I was not feeling comfortable with andrew ng

[@SumanSadhukhan-md4dq]

Can anyone differentiate loss and coss function?

[@JyotirmoyGupta-x5r]

@@SumanSadhukhan-md4dq Loss function is the error expression when considered for a single data point. When we sum up all the errors over all the data points, we get the cost function. So, basically, cost function is when we sum up the loss functions of all the data points. Hope this makes sense to you.

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u r best mentor/teacher i ever came across for data science....

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It takes patience, endurance and talent to be a teacher, but you make it look so easy day after day. I hope you know just how much we all appreciate you.

[@ritwikgupta7540]

Still halfway trough the video, but I feel necessary to comment here. This is by far the best explanation of Loss function and the intuition leading up to it. I have enrolled in paid courses to learn this, and let me tell you the quality of explanation in this 53 min video is better than any other resources out there. Kudos to you...keep shining Nitish!!

[@HealthyEveryday-to5dt]

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[@tusharsub1000]

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[@campusx-official]

Glad you liked them

[@Salman_Shaikh43622]

Dear Nitish, You are best DS mentor. Thanks for creating the channel for those who seeks the job in DS.

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Hats off to you sir. Apart from immense knowledge, your patience and ability to simplify abstract topics is outstanding. You are a gifted teacher. Thank you is not enough.

[@anonymousxyz3856]

You are amazing!! Just the way we want the lectures to be!! When you take care of uppercase and lowercase chars while writing terms like X_train, y_train, it reflects your in depth understanding of the subject and the notations one should follow. You will reach great heights.

[@paruchuriradhakrishna7759]

Awesome vedio I couldn't this much detailed explanation even from great KZbin data science teachers

[@preetiughrejiya3045]

I think the way you have cleared my concepts has given me more confidence to talk on ML models and their fine tuning. Really very intuitive understanding.

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[@saptarshisanyal6738]

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[@user-is2qg6yh2b]

You explained every concept articulately. Thank you

[@techtonic3652]

You are awesome in explanation I have never learn anything as simple as you explained. you made the complex things for me very simple. You are awesome.

[@sumitwarkari4455]

Very good explanation for the linear regression algorithm. You covered the math behind it. I never thought that i could learn how algorithm works in the backend. Thanks for the explanation.

[@manandesai6404]

I took one course which has over 1M students still I find the course rubbish, like they did not go any deep. And here is this guy with just 220k subscribers(while commenting) and have god level teaching skills and going very deep in what and how. You deserve more than what you are getting. Hopefully people will find this channel and you get more for what you are doing. You are a just amazing 🔥

[@numanakhtersiddiqui6573]

best tutor for ML on youtube. know one teaches with this much depth

[@saptarshisanyal6738]

As of today this video has 8k views. But i am sure in the next 1 year it will cross 1 Lac view. This is the best explanation of cost function derivation.

[@srikrithibhat1999]

15:54 Actually it should be yi^, Because that line has been drawn by the model, so it will be a predicted value right? And the above point should be yi. I think you have said it ulta. Could you please reply to this? And all your sessions are awesome. Thank you so much for such a great explanation.

[@kalyanikadu8996]

Such an Amazing teacher with such an incredible content and explanation. Very grateful to you Nitish! A very biggg Thank you too you.

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Finally I found the best teacher which will help me in ml journey

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machine learning is fun right now but time consuming too. All thanks to you sir.

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Awesome videos, You are the best teacher for data science

[@Aquib_Aftab_7903]

Loved ur explaination sir, Really got a taste of calculus after so long.

[@rish725]

That was exceptionally good... Thank you for this amazing explainer

[@bakkaabhilash5393]

Woww..... ! Satisfied with full clarity. Thank you sir.

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No words to say after watching your videos just love you brother...

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[@SumanSadhukhan-md4dq]

Wow... I got full clarity now😊

[@sameerpandey5561]

Clean and crisp Explanation

[@namansethi1767]

Thanks sir for this explanation on linear regression

[@rajaneeshray7502]

bhai kya teaching style superb.

[@sayanNITdgp2025]

you have created a gold mine...

[@pankajitm]

Brother you nailed it in explanation, best tutorial

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the way you teach is awesome

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bahut hi pyara video tha sir thankyou

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What a great explanation 👏🔥 Hats off 🫡🙇‍♂️

[@coding_world_live9]

Man dil jeet liyaa❣️🔥

[@jaikumarpritmani6596]

thankyou so much sir for adding so much value...

[@sober_22]

The best Explanation ever!

[@descendantsoftheheroes_660]

Thanks sir God bless you ..Keep continue

[@chiragjain5630]

thank you sir for all such beautiful content. there is a small mistake at 16:00. predicted and actual values are named incorrectly

[@chitrakshi2587]

Next Level Explanation.......thanks for sharing🫡🙂‍↕️

[@sahaji-bi7qi]

great learning bro, maja a gaya , love you bhai.

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The most underrated data science channel on KZbin

[@milindtakate5987]

Clear and concise explanation!! Will it be possible to create one lecture series on in-depth Python? I have checked the one uploaded by you. But it has some missing lectures. Also, in some lectures the board is not visible. Thanks in advance!

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Best Teacher Ever!

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Awesome Sirji, tuse great ho

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Hidden Gem On KZbin

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best video for LR maths

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sir, hats off to you

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Thank you sir 👍

[@0Fallen0]

Hey can you make a video on Custom Estimators that are compatible with Scikit-Learn? defining our class like SimpleReg(BaseEstimator, RegressorMixin): so we can "technically" use it in pipelines? I tried but it isn't passing the check_estimator test by Scikit-Learn.

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If you were our maths teacher, then maths would never have been a darawana subject as it is considered to be now😂

[@sandipansarkar9211]

finished watching

[@deeprajmazumder6261]

Hi sir, You said that in OLS we don't use approximation process like differentiation etc, but while explaining for OLS, you went to explain gradient descent and then proved the formula for OLS. I have a doubt in that sir.

[@maths_impact]

Wonderful sir

[@shanrock1021]

excellent !

[@sudipgautam7471]

@ 16:00 there is small mistake If predicted is represented by hat symbol and actual by not hat Then y hat must be below and y must be above in y-axis line

[@zerotohero1002]

Your the best

[@arshad1781]

Thanks

[@meethirpara4707]

Your explanation is mind-blowing but my question is when we square all the data point then line will be form according to the squared data but our actual data is non square how it will adjust according to our real data

[@infinity2creation551]

Sir apney (y hat) ko ulta likh diya (y hat) toh actual value hai and (yi) jo model predict kiya ..but ap bol sahi rahe ho likh ulta rahe ho syd...(yi) upr hoga and (y^) niche hoga q ki nichey wla model predicte kr rha is liya niche wla hoga.. Or di =(yi-y^) hoga or yi upr hoga and y^ niche hoga.. 15:30 Plz reply

[@niketasengar9191]

thank god someone noticed, i was sooooooo confused T_T

[@infinity2creation551]

@@niketasengar9191 yaah so mujhe abi tak solution ni mila..! Apko mila?

[@ameerrace2284]

Will you b working on sgd regressor in upcoming videos?

[@akshaykanavaje474]

that's what we called learning algorithms from scratch. sir, can u tell us which book you preferred to learn this from? just love your content.

[@campusx-official]

Will soon be uploading a video on this topic.

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Best sir 👌👌

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[@shivoham5939]

sir i have one doubt sir if we equate the slope of the func to zero or derivative to zero this means that it can be either maxima or minima . please explain this sir

[@sachin2725]

Hello Sir, XGBoost is not included in playlist, could you please make a video on XGBoost ?

[@Kishore6413]

In the error function, along with m and b, y also depends on x, right?