How to Frame a Machine Learning Problem | How to plan a Data Science Project Effectively

Choosing a machine learning method to implement data is not the easiest of processes. It is essential to first understand the precise business problem and its objectives. For instance, understanding what needs to be predicted and understanding potential outcomes is critical.
One also needs to know what data should be used to train a model, among other factors. Such considerations help with the framing of a machine learning problem. In this article, we will look at how to frame a machine learning problem correctly.
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⌚Time Stamps⌚
00:00 - Introduction to framing the problem
2:24 - Case study example of Netflix for churn rate
6:23 - Business problem to ML problem
7:08 - Types of problem
12:24 - Current solution
13:33 - Getting data
15:09 - Metrics to measure
17:15 - Online Vs Batch?
19:15 - Check Assumptions
✨ Hashtags✨
#100DaysOfMachineLearning #MachineLearningFullCourse #MachineLearningInHindi

[@saumyashah6622]

The thing which you mentioned today as a netflix case study, I figured out the same thing with udemy last month. I am an avid learner from udemy. But they stopped giving me discounts, so i tried to trick the algorithm by keeping courses in the cart and then not buying them for long time, also instantly refunding 4-5 courses. So the algorithm worked as you described and now I am getting full fledged discounts.

[@khemrajpatil5683]

That's the cool move!😃

[@ipranavprashant]

Woah that's interesting😂🎉

[@msgupta07]

00:00 Introduction to framing the problem
2:24 Case study example of Netflix for churn rate
6:23 Step 1: Business problem to ML problem
7:08 Step 2: Types of problem
12:24 Step 3: Current solution
13:33 Step 4: Getting data
15:09 Step 5: Matrics to measure
17:15 Step 6: Online Vs Batch?
19:15 Step7: check assumptions

[@iam_shiv07]

This video is really very important, because most of us, while doing project have mentality like "start krte h aage jo probelms aayengi solution dhoondh lenge" but no, we have to frame a path, As a Lead Data scientist we have to figure out everything.

[@GamerBoy-ii4jc]

Sir you are greate sir ever on utube .May Allah(God) give you the reward of your effort.

[@balakrishnanr648]

I am really grateful that with ML, you are also sharing good practices + Experience which is not that easily available.
Really telling, this is a fantastic content, other click baiters cant give the knowledge that he is giving.

[@rimadutta5144]

thank you sooo much for creating this amazing playlist again. you are awesome. one of the best educator on TH-cam.

[@akshaysarbhukan6701]

One of the best data science videos I've come across. Thank you so much for this.

[@akash.deblanq]

These type of intuitive approach videos are so important and you did an amazing job. Thank you for the video.

[@shahrukhahmad4127]

Best best best channel I found for Machine Learning. Thank you for all your efforts sir❤️❤️❤️

[@shwetan1250]

Those , who wants to learn data science but not able to motivated ourselves so watch this addicted playlist . i am gaining so much knowledge , learning so many concepts . very nice playlist . Thank you so much sir for this interesting playlist.

[@shreyanshgaurkar9107]

i really found an amazing tutor for data scientist really great sir , i feel lucky that i watching your videos it helps me alot for gaining such imp knowledge , such a great tutor

[@talhanadeem7957]

Thanks for sharing your knowledge in the most understanding way!!!

[@paragvachhani4643]

Sir, DS ki life ki feeling dila di...aapne....thank u nitish bhru...

[@grithijain132]

Thank you campus x for your support and dedication

[@rajalakshmisundaram5278]

Amazing content....God bless you...I'm binge watching your videos...playlist is awesome....

[@siyays1868]

Wondefully explained! Wonderful video as always. Thanku so much sir. Very greatful to u & ur channel & always will be. I considers myself very lucky to have a great teacher & awsome mentor in the form of u. 🙏🙏

[@arun5351]

Great insights mate and awesome playlist. Keep up the good work👍👍

[@shivamkumar-ly4jk]

sir you are going to be the next physics wallah.😇
very well explained everything

[@kaustavbasu]

Thanks for the playlist! I'm really grateful to you for providing us such valuable lectures. :)

[@TheboredConsultant]

This is really helpful. This is the exact structure I was looking for so I can structure my thoughts. Thanks you :)

[@khemrajpatil5683]

Great video! I am very grateful for your all videos. Thanks much!☺

[@harshitasingh902]

Such an amazing playlist. Made my Data Science journey so easy going. Thankyou sir

[@pratikbhise3228]

you are just awesome. very perfect playlist
Thank you So much

[@memesjunction572]

Sir jo aap last mei motivation dete ho achha lagataa hai...

[@narendraparmar1631]

Thanks for sharing this knowledge.
Thanks sir😀

[@aadilrafiq9428]

i don't know about Netflix but your content is the one of the thing which i do not wish leave

[@akritisaha25]

sir , you teach veryy well. THANK YOU SO MUCH for all your efforts!!

[@AbdullahAlMamun-jm4qm]

Seriously You are great ...

[@nishantchaudhary7528]

I really really loved the content... superb!!

[@accurateboy]

Love u brother❤. u r awesome

[@Softweb-ci9bf]

This video is best , accouding to future data science job , after a exprience you have been leadership posstion , thanks sir

[@JainismWithUnnati]

Best strategy to introduce topics to a newbie❤❤

[@yashjain6372]

Bhai you are doing awesome work. Decided to watch complete playlist. I hope you could be active on Linkedin as well

[@naturevideos8029]

thank u sir love ur every video. the way to explain everything with so much ease this is outstanding again thank u so much. xo xo xo.

[@varunahlawat9013]

Insightful!

[@sMKUMARSAISKLM]

wow nice content sir

[@AltafAnsari-tf9nl]

Excellent content 👌👌👌

[@Rahul-tk7ke]

great sir!!!

[@sinsyearcitizen3578]

Watched till the end

[@MuhammadJunaid-yr8jd]

thanks a lot sir

[@dileepkr6069]

Best explanation ❤❤❤❤❤

[@drsnehaljk]

Great content! Can't thank enough

[@rahulnarayan6878]

thank you so much sir!!

[@Moosakhan622]

sir we are watching the whole video but way thanks

[@JACKSPARROW-ch7jl]

Thanks 👌🙌😉

[@manishpingale6558]

Privileged to be getting this content for free!

[@soumyajyotirouth5134]

great video sir😁

[@arpitajana947]

Thanks

[@usmandotem]

Sir I am a student in pakistan. I am studying from the top IT university in pakistan, FAST NUCES. but the content, the learning you are providing is not comparable to any TH-cam channel till now!! and it will never be. JUST WOW!! the concepts you have, the way how you teach is incredible (considering data science is a new field)

[@usmandotem]

please let me support you. I don't want to watch this playlist for free

[@sandipansarkar9211]

finished watching

[@tanmayshinde7853]

is there any need to learn c++ or java for interview in big MNCs for data scientist role.

[@nikhilsuryawanshi392]

dekh rahe hain, pura dekh rahe hain, aur dekhenge..

[@ashishagarwal-nj8ud]

Thanks!

[@yashjain6372]

good

[@talibdaryabi9434]

Now I understand what the big picture is and how we must see it.

[@talibdaryabi9434]

I put commend to hope that TH-cam algorithm recommendations suggest this playlist to more people.

[@amansingh-ih2by]

sir
recommend any book for machine learning for beginner

[@ashishmhatre2846]

Day1 - already completed till Day 15 ! Awesome videos

[@PankajKumar-yt5qp]

can we get the slides in which you have written ?

[@joffie3653]

Can you please add the English subtitles please for all these videos

[@adarsh_kumar_sharma_8638]

@campusx
sir can you provide this files or notes

[@krishnakanthmacherla4431]

Done

[@babasahebunde7425]

Sir,please make video on ray.io for Machine learning pipelines

[@FocusBankExam]

Sir mujhe aapse pyaar ho gya hai...

[@arman_shekh97]

Sir code machine learning expert ko jada Karna padta hai ya programmer ko plz tell me sir

[@campusx-official]

Amount of code to programmers ko hi jyada likhna padta hai

[@MRAgundli]

done

[@namduong6028]

Please eng-sub

[@d1pranjal]

If Netflix saw this video earlier....they'd have avoided their subscriber loss 🤣🤣