Implementing Machine Learninng Pipelines USsing Sklearn And Python

github: github.com/krishnaik06/Pipeli...
Pipeline of transforms with a final estimator.
Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be ‘transforms’, that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using memory argument.
The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step’s estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to 'passthrough' or None.
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[@krishnaik06]

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[@isaackodera9441]

Couldn't be more grateful than this. This process in its entirety solves and prevents data leakage. With you, learning is always guaranteed. Time for implementation. A happy subscriber.

[@sirginirgin4808]

Many thanks. Kindly keep the hood work. I was following you for the last few years since you started your first videos by recommending data science books and channels ect... Yor proffisional videos are getting better and better. Many thanks again for your github link too.

[@PM-cs6jq]

thank you Krish. Such an awesome teacher you are! Makes learning so much more fun!

[@anirudsaichenna3158]

Hello Krish, Thank you for your detailed explenation. You are an amazing teacher, the content, the approach and intent of making sure that it reaches the learner, actually I can add lot more qualities of this video if I want to continue. I really appreciate your effort in making the videos on ML. I passed through many other youtube channels for this particular topic, and honestly I felt like had I come to this video first I would have saved lot of my time. Once again thanks alot. Stay blessed.

[@rameshcheppali4353]

This is one of the best video on Pipelines on you tube .Very Nice .Well Explained and content is very good.

[@moinuddinkhan928]

I am from aligarh uttar pradesh......background commerce......I am seeing ur videos to learn data science.......i think am the only person from my city........right now seeing your python playlist.......and I want to become a data scientist......pray for me.......inspired by you and campus X........take care

[@longtruong9935]

the best pipeline video ever, thanks for sharing

[@saifuddinlokhand5769]

Useful Concept with proper explanation

[@yaswanthkosuru]

i learned a lot of new things which makes machine learning project in an organized manner.

[@narottamsaini6951]

Hi Krish, in next video plz also try to incorporate how to add custom made function doing loading of file, doing date formatting and removing invalid record as a part pf pipeline!!!

[@dsdjiitian]

Thank you sir for this amazing video on pipeline it really helped me in understanding the concept of pipelines 🙏

[@pritamrajbhar9504]

This is what I was looking for, thank you so much krish sir.😊

[@0SIGMA]

I had forgotten this but thanks sir!!!!!

[@bbagchi3771]

Excellent video. Thanks for sharing.

[@radhekrashna2148]

Thank you so much for very good quality content

[@xygameming]

Really awesome sir your way of explanation . We loved it.🎉🎉🎉

[@Xnshau]

Thank you Krish 👍 nicely explained

[@sriramasatya1393]

Sir.. Thank you very very much.. you explained the procedure so well!!

[@vargabghosh5497]

your videos make things easy

[@harshitsingh715]

This is the best video I have gonna through for this topic sir, please create it with tensorflow for deep learning

[@kasoziabudusalaamu50]

thank you for sharing the knowledge. I have really learnt a lot.

[@yashesh7264]

great stuff sir we love you

[@ritugujela8345]

sir, can you please make a video on making an end to end project using ML pipelines that includes all techniques like missing value imputation, OHE, Feature Scaling, Feature selection and linear regression ?

[@shashankhegde1258]

excellent !. THanks

[@phoenix4939]

Really Good Video!

[@ashraf_isb]

At 6:32 sec when Krish says like, stopping video to like and then continuing

[@HARSHRAJ-2023]

Looks useful 👍🏻

[@msgupta07]

This is the video I want because pipelining related videos are not that good on KZbin. Plz.. kale it with grid search

[@aniruddhmaitra1728]

If we have a NN model, how will we make it a part of the pipeline? Awesome video.

[@bivasbisht1244]

amazing

[@Pune_Tithe_Kay_Une]

First view biggest fan machine learning

[@dingaroo2003]

Hi Krish, great video again! How can I add a metrics like ConfusionMatrix to my pipeline? Is it to add another pipeline?

[@kwenevdavidapine4661]

Thank you for this explanation. I have one question; when do we need to use Union? Can it be used in place of make_pipeline? Thank you.

[@sandipansarkar9211]

finished watching

[@user-ur2en1zq4f]

thanks sir

[@muralikrishnapolipallivenk2572]

Hi Krish, great video, very good explanation, one question is how do we define the pipeline and predict if one of the columns is a text.

[@Sanjay-xq5xr]

Eda

[@tejasaiyarlagadda644]

Hi bro...please make video for datascience as fresher to create a resume pls....

[@siddhantkohli5063]

Sir what are your thoughts on IITM online bsc data science degree is it worth it ?

[@rohinik2223]

Hi,thanks for sharing Can you share mlops with gcp videos plz Thanks

[@omkarbelpatre5]

sir apne bola tha data analytics roadmap ki video Dalunga sir ?

[@VARUNyoutube]

What is the difference between TechNeuron FSDS cousre and FSDS bootcamp

[@prateekkumar.1325]

what if i would like to add std transformer,pvc, linear regression,KNN and svc .How shall i proceed,sir?

[@lakshmiv5745]

explain pipeline for embedded system example and types and real life application. What uses

[@ajaykushwaha4233]

Hi Krish, is it compulsory to write program using pipe line ?

[@sivachaitanya6330]

Very late doing this video krish...

[@sandipansarkar9211]

finished coding

[@juancastillo5571]

but you hadnt fit the colum pipeline.... why????