00:02 Deep dive into Scikit-learn and its potential for Data Science 02:29 PsychLearn is about algorithms and preprocessing in machine learning. 08:13 Estimators are objects with the fit method 11:19 There are two types of estimators: Predictor and Transformer. 16:51 Predictors and transformers in SK Learn 19:30 Custom estimators are user-defined classes in Scikit-learn. 24:17 Creating custom estimators in scikit-learn 26:36 Understanding Scikit-learn for Machine Learning 31:46 Custom estimators in Sklearn 34:05 Understanding and implementing Scikit-learn Estimator class 38:49 Custom Estimator and Mixins in Sklearn 41:10 Understanding custom estimator in machine learning 46:09 Transformers are used to modify and create new features from the original data set. 48:49 Transformers in machine learning can be customized for specific needs 53:54 Understanding standard scaler for data normalization 56:32 Creating custom transformers using Sklearn 1:02:33 Introduction to creating custom transformers 1:05:47 Inheritance and creation of custom transformers in Scikit-learn 1:11:36 Explanation of applying transformers in Scikit-learn 1:14:19 The column transformer in Scikit-learn is capable of handling heterogeneous data types. 1:19:51 Column transformer is used to apply transformations to different columns. 1:22:51 Understanding column transformers and pipelines in scikit-learn 1:28:35 Understanding Feature Union and its Transformations 1:31:26 Using Sklearn to apply multiple transformations on columns 1:36:10 Understanding feature union in pipeline 1:38:30 Understanding the feature union and pipeline in Scikit-learn 1:44:07 Building a pipeline for multiple transformations 1:47:12 Understanding the pipeline design for machine learning 1:53:00 Understanding the process of transforming and selecting features in machine learning pipelines. 1:55:11 Applying feature union, scaling, feature selection, and logistic regression in the final pipeline
It its null at random then fill when column is important or uda de. U check plot heatmap of null values to check randomness. Probably udana sahi h. U should check acuracy with imputation and without imputation. If accuracy is high with imputation then sahi h. Nhi to udana sahi h
Hi sir first upon thanking you for all your videos and teaching. Sir i request you please upload one detail video on YoloV8, it's file structure how to create our own files in this architecture
hello sir myself zeeshan khattak from pakistan i dont know how can i express my felling in words for you . mai khud bachoo ko data science parata ho awr sub ko apka channel recomend karta ho bas sir alllah apko lambi awr sehat yab zindagi de kash hum ek country mai hote shayad apsi ek bar molaqat to hote but any way long live sir best wishes from pakistan ,pakistan zindabad india payindabad ❤❤❤❤❤❤💕💕💕💕💕💕
Thanks DSMP 2 Students ❤
thanks to all students
Thanks DSMP 2 students and Sir ,,,,,, Sir is there is any tutorial for tensorflow then please come up with that
Thank you 🎉🎉
Been using scikit learn for 3 years,never knew we can explore such depths in this library. A teacher we all deserved, when we were in college:)
OMG OMG OMG OMG OMG Sir kitni tarif kare ab aapki sir. Please puri life aese hi teaching karte rahena 😀😀😀.
00:02 Deep dive into Scikit-learn and its potential for Data Science
02:29 PsychLearn is about algorithms and preprocessing in machine learning.
08:13 Estimators are objects with the fit method
11:19 There are two types of estimators: Predictor and Transformer.
16:51 Predictors and transformers in SK Learn
19:30 Custom estimators are user-defined classes in Scikit-learn.
24:17 Creating custom estimators in scikit-learn
26:36 Understanding Scikit-learn for Machine Learning
31:46 Custom estimators in Sklearn
34:05 Understanding and implementing Scikit-learn Estimator class
38:49 Custom Estimator and Mixins in Sklearn
41:10 Understanding custom estimator in machine learning
46:09 Transformers are used to modify and create new features from the original data set.
48:49 Transformers in machine learning can be customized for specific needs
53:54 Understanding standard scaler for data normalization
56:32 Creating custom transformers using Sklearn
1:02:33 Introduction to creating custom transformers
1:05:47 Inheritance and creation of custom transformers in Scikit-learn
1:11:36 Explanation of applying transformers in Scikit-learn
1:14:19 The column transformer in Scikit-learn is capable of handling heterogeneous data types.
1:19:51 Column transformer is used to apply transformations to different columns.
1:22:51 Understanding column transformers and pipelines in scikit-learn
1:28:35 Understanding Feature Union and its Transformations
1:31:26 Using Sklearn to apply multiple transformations on columns
1:36:10 Understanding feature union in pipeline
1:38:30 Understanding the feature union and pipeline in Scikit-learn
1:44:07 Building a pipeline for multiple transformations
1:47:12 Understanding the pipeline design for machine learning
1:53:00 Understanding the process of transforming and selecting features in machine learning pipelines.
1:55:11 Applying feature union, scaling, feature selection, and logistic regression in the final pipeline
great
I really appreciate your efforts sir! We hope for more videos in the future too! thank you to paid students 3000 times....
Nitish and krish naik are very similar in looks😂
jo iss sir se python sikhe hai give me feedback about his python course please
kyya kya sikhana padega iss ko sikhane se pahale
Can I watch this even though I m a beginner?
Thank You ❤
Thanku for sir and those students who this allowed the persmission...and sir is very great
Mujhe ek doubt hai, ML ke ek column mein 35% missing values hain. To kya karu kya poora column uda du?
If it's significantly important column, try to impute the values or if not you can drop the column
Depends on column importance. If it is not necessary then remove else impute values
uda de !!
It its null at random then fill when column is important or uda de. U check plot heatmap of null values to check randomness. Probably udana sahi h. U should check acuracy with imputation and without imputation. If accuracy is high with imputation then sahi h. Nhi to udana sahi h
thank you sir , and plz share if anything is important for us
Thanks sir anN DBMS 2 students
Sir dsmp2 lifetime access hai !
Thanks for this, sir❤
Great work sir
Thanks paid students
Please free more video
sir. pau lagu i am very lucky to have a teacher like you
Crose val kya h sir bataye
is this for beginner?
Thank you to DSMP2 Students ❤
Thanks DSMP students, showed big heart ❤
Again Excellent way of Teaching , Even a non It background person can also understand .
DSMP2 THANKS
sir pls start power bi
Hi sir first upon thanking you for all your videos and teaching. Sir i request you please upload one detail video on YoloV8, it's file structure how to create our own files in this architecture
Thank you so much for approval all ma dear DSMP 2 Paid students .. really appriciate your votes ❤
Great Sir जी 👍
Thank to all of you guys
And thanks sir
Please add list of topics you thought it's realy helpful for guys want to enhance there knowledge
thank u all the paid students 😇☺
nitish can you please upload nlp remaining lectures which are NER,Topic modeling NLP based?
'Promo sm' 🎊
Thank you sir...
Pls make a video on using flask framework for beginners as well:) creating a mini project like e library
Just like building custom dataset using pytorch inheriting Dataset module.. and A lot more examples
Thank u Sir❤❤
Sir please put all these videos of "Data Science mentorship program" in a playlist
thank u for explain in simple way with good ex. 🙏👍
hello sir myself zeeshan khattak from pakistan i dont know how can i express my felling in words for you . mai khud bachoo ko data science parata ho awr sub ko apka channel recomend karta ho bas sir alllah apko lambi awr sehat yab zindagi de kash hum ek country mai hote shayad apsi ek bar molaqat to hote but any way long live sir best wishes from pakistan ,pakistan zindabad india payindabad ❤❤❤❤❤❤💕💕💕💕💕💕
why we are doing .toarray() in column trnformer?
Amazing sir
please bring a crash course on machine learning sir it really needed
Bhai aak project banao drs system par jo cricket ne use hota hai using ml .
sir i want to be a member of DSMP 2.0
is the DSMP 1.0 the prerequisite..??
yes because DSMP 2.O is advance version of DSMP 1.O
@@rahulsaini1112
Hello Bhaiya aapne DSMP 2.0 mai enroll kiya hai kya??
@@PrakashChildhood yipp brother
@@rahulsaini1112 Bhaiya Can you help me I want learn from DSMP 2.0 but not afford
Sir we are working on ai sorting machine please can u guide us
Thanks to DSMP2 students and Nitish Sir
Thanks DSMP 2 Students✨
Thankx sir and your paid student...
sir.. kiya or videos bhi ayn gi related to Sklearn..??
Can't Thank you enough for this sir❤
Thanks you DSMP 2 Students.
Thanks to dsmp 2 students and also to u sir ❤❤❤❤❤❤❤❤❤
Thankyou sir, thank you very much😢😢😢
Apka pacakage kya hy..? Aur ap kis company mei kaam kr rhe ho
Make a video on hugging face and langchain
One of the best video on this topic.
Thank you so much everyone! ❤
Thanks DSMP 2 Students 💗💗💗💗
Thanks sir for this honourable work ❤
Thanks a lot everyone
thanks a lot dear campusx cohort students and the mentor
Thanks DSMP student ❤
Thanks dsmp students
Thank you for your efforts, sir !!!
Thanks ❤
God of kindness ❤❤
Thank you all
Thank you Sir
TY
Plz powerbi course start kro sir 😢😢😢
yes sir please..we really need this
32:08
Sir Aapne ROC Curve And AUC Curve kaya Use Hai Video Banaya Hai kaya
ruclips.net/video/gdW6hj9IXaA/видео.html
@@campusx-official Thank you ☺️
I hope so you also teach Mathematics
check out his channel, he has a dedicated playlist for that.
I have learned a lot from you. Thanks for everything, love from Pakistan 🇵🇰
You are already genius Thx again Love from Pakistan
Thnx to dsmp 2 students ❤️❤️❤️