the best part about your teaching is the path to follow, that you show before starting out something I have wasted a lot of time going round and round while trying to learn ds ml it saves a lot of time if there's a clear path laid out and you know what you have to learn. Thank you so much man, you are amazing. :)
Great content, you have put everything in structured way which is great part of your teaching and teaching in very simple way, I will watch each and every video more than 5 times, God bless you for educating others.
Sir can I please ask why did you covered data cleaning part after EDA ? I'm having a little confusion about it can you please tell. Is there a specific reason ?
Sir web scrapping ki ek apor video bna dijiye isse pahle wala samjh me nhi aaya wo Jo aapne recorded dala tha plz sir mai aapki Puri playlist follow kr raha hu
Can anyone help me understand the difference between Feature Transformation and Data Preprocessing? Aren't both of these doing the same thing like Missing value imputation, Outliers detection , Scaling ? If we have already done data processing, why do we need to do feature transformation?
there is a catch, Data Preprocessing involves Data Cleaning,Scaling,Encoding Categorical Variables,Handling Imbalanced data etc. Feature Engg involves creating new features or transforming existing feature such as deriving features like ratios,Dimensionality Reduction using PCA,Feature Selection,Feature Extraction
I have paid for some courses, its fully waste. urs is next lvl of understanding, man let me get an internship, I will surely transfer u a part of small amount as GuruDhakshana
Guys I have doubt, can anyone help. For scaling data: we have numerical column and categorical column are encoded in to numerical. So scaling need to done only on numerical column or on encoded column as well
As a symbol of thanksgiving , i never skip ads on your youtube video , i will let it play in full,😂😂😂
And also click it
Yes I also started watching ads and clicking sometimes
the best part about your teaching is the path to follow, that you show before starting out something
I have wasted a lot of time going round and round while trying to learn ds ml
it saves a lot of time if there's a clear path laid out and you know what you have to learn. Thank you so much man, you are amazing. :)
I you ever come up with a paid course. will definitely pay. Thats how good your content is
you can still pay him
Ma sha Allah bahi, I m from Lahore Pakistan and salute your dedication,Allah bless you and grant you health and success ameen regards
The best Playlist for Machine Learning!
You are the Best
this YT channel is hidden treasure........protect it at any cost
Excellent work. I am not an Indian but I know Hindi :) I can say this is the best ML path!
you are definitely abdul...😂😂😁😁
@@ThrasosLogosTechRealm Abdul???
never been disappointed by your video, always crystal clear and in depth explaination. Truly amazing
very amazed sir....it is all your hard work of many years ....you are giving us two in a minute time.....😊
Great explanation....the way you explain things are pure gem...
the best channel for everything about ML ,DS
My heartful thanks to you brother. Great stuff and awesome delivery.
Great content, you have put everything in structured way which is great part of your teaching and teaching in very simple way, I will watch each and every video more than 5 times, God bless you for educating others.
Excellent overview and superb teaching skill 🙏
You are the best at teaching. Content excellent 🎉
Very nicely explained.very much excited to move with further videos
Beautifully Explained Every aspect of Feature Engineering, make it so simple for us to understand
awesome...crystal clear...thank you sir
Very clear explanation.
Wow, you are really Amazing!
I think aap to kisi pagal ko bhi samjha sakte ho
Thank You for your Hard work
That is a great explanation with the example, which I generally don't find.
sir your contents are very good. if you could add english subtitles it will benefit everyone. kindly consider sir
iam so confused about what is feature engineering, what are the techniques , But after your video crystal clear sir, l love your clarity in teaching.
These videos are best.
Thank you!!😃
This lecture helps a lot.
Thank You😀
Awesome bhai Love you for your efforts...
beautiful explaination.
Thanks Nitish for giving us such a wonderfull content
Course Started : ML
Lecture-01: 14/08/2024
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Lecture-23: 23/08/2024
excellent information keep going by creating like this videos
Excellent video!!
Sir can I please ask why did you covered data cleaning part after EDA ? I'm having a little confusion about it can you please tell. Is there a specific reason ?
excellent information
Excellent !! 👏👏
Thank you so much sir 🙏🙏🙏
sir please create a complete playlist on recommendation system with alot of projects please sir please. I request you
awesome teaching
as always, BRILLIANT
Just Awesome
sir, i really appreciate your teaching. I want to know the major difference between standardization and normalization feature scaling techniques
Nice...
aaj ki night feature engineering ki study kr ne liye...kurban
Thanks Sir 😃
Dope Content Quality
THANKS!!
very understandable video
much intuitive
Sir web scrapping ki ek apor video bna dijiye isse pahle wala samjh me nhi aaya wo Jo aapne recorded dala tha plz sir mai aapki Puri playlist follow kr raha hu
Please share the one note for these lecture. It will be very helpful
As per your explanation, feature construction & extraction are the same right? Otherwise, give me the difference.
great vedios brother.. if you have time post vedios on MLOops.
Can anyone help me understand the difference between Feature Transformation and Data Preprocessing? Aren't both of these doing the same thing like Missing value imputation, Outliers detection , Scaling ? If we have already done data processing, why do we need to do feature transformation?
there is a catch, Data Preprocessing involves Data Cleaning,Scaling,Encoding Categorical Variables,Handling Imbalanced data etc.
Feature Engg involves creating new features or transforming existing feature such as deriving features like ratios,Dimensionality Reduction using PCA,Feature Selection,Feature Extraction
Sir very nice
can you provide us the OneNote Notes for 100 days of ML?
thanks sir
Hi bro can you please help me how I can convert Unstructured logs into structured format and do analysis of it, like if errors are their
finished watching
I have paid for some courses, its fully waste. urs is next lvl of understanding, man let me get an internship, I will surely transfer u a part of small amount as GuruDhakshana
how will they help to make descision making me more confused.
Feature Selection video is not there
Thanks
awesome
Sir can you please share this PDF file to understand the topic for revision
😍😍😍😍the best
Sir do you have ppts of all the lectures
What is the difference between construction and extraction
y u so good bro?
Hi Sir, feature selection ka vide missing hai, kindly upload.
Will do it in a few days
Sir please you make a full stack data scientist course on udemy
Guys I have doubt, can anyone help.
For scaling data: we have numerical column and categorical column are encoded in to numerical. So scaling need to done only on numerical column or on encoded column as well
Where is playlist consisting day 1 to day 23 videos.
th-cam.com/play/PLKnIA16_Rmvbr7zKYQuBfsVkjoLcJgxHH.html
@@campusx-official Thanks
confusion between construction and extraction features
Sir can you please provide this file or notes
Done
day2-date:10/1/24
❤
sir please launch a telegram group
feature contruction and feature extraction same hi lag rhe hai
Yup!! completed it guyzzzzzz
done
outlier ❌ sharma ji ka beta ✅
😂😂
Why the caption is in English and the video in Hindi. Wtf
"Sharma ji ka beta" 🗿
this a little scary though
where is English 😥😥😥???...
if you talk in eng
My heartful thanks to you brother. Great stuff and awesome delivery
Thank you sir
thanks sir