Datavisz @Datavisz

#66daysofdata. Newbie. Machine Learning Enthusiast Joined October 2020

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Datavisz @Datavisz

2 years ago

@msrtcofficial 2 tas jhale bus chi vat baghtoy. Pune Nashik route. 11 chi shivai ajun yet ahe. Ashi tumchi seva ahe. Sarkari Karan karaychay yanna. Velet bus soda pahila.

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Datavisz @Datavisz

4 years ago

Day 120 of #66daysofdata : Read few articles on exponential distribution and poisson distribution by @aerinykim. towardsdatascience.com/what-is-expone…

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Datavisz @Datavisz

4 years ago

@ashramachandran Are you ready to overwork once you accept this position?

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Datavisz @Datavisz

4 years ago

Day 119 of #66daysofdata: Finished the section on sql joins and chapter 1 of reliability engineering text.

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Datavisz @Datavisz

4 years ago

Day 118 of #66daysofdata : Watched a video on how simulation and AI techniques can be used in the future by @ANSYS

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Datavisz @Datavisz

4 years ago

Day 117 of #66daysofdata: Back to the udacity course on sql. Revised joins.

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Datavisz @Datavisz

4 years ago

@dataQueen_pend Wishing you the best!

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Datavisz @Datavisz

4 years ago

Day 116 of #66daysofdata : SQL Joins

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Datavisz @Datavisz

4 years ago

Day 115 of #66daysofdata : Learning sql from a free Udacity course.

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Datavisz @Datavisz

4 years ago

@dataQueen_pend @DataCamp Great going Kira!

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Datavisz @Datavisz

4 years ago

Day 114 of #66daysofdata: Presented on a use case of PCA in my org.

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Datavisz @Datavisz

4 years ago

Day 113 of #66daysofdata : Watched statquest videos on ridge, lasso and elastic net regression

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Datavisz @Datavisz

4 years ago

@ashramachandran @TheRanveerShow No more posting out new content but I like to listen to episodes of @LinDigressions

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Datavisz @Datavisz

4 years ago

@marktenenholtz Thanks

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Datavisz @Datavisz

4 years ago

Day 112 of #66daysofdata : 1. Learnt about dimensionality reduction techniques. (LDA & PCA) 2.Nominal and One-hot encoding for categorical variables.

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Datavisz @Datavisz

4 years ago

@bhutanisanyam1 Pushpa-giri

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Datavisz @Datavisz

4 years ago

@ritesh_panditi Data leakage can happen if we use the same transformation parameters on the data set and then split it into training and test set

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Day 111 of #66daysofdata: Learnt about sklearn.pipeline.Pipeline which applies pipeline of transforms with a final estimator. This can come in handy when you would want to avoid data leakage while applying data transforms

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Datavisz @Datavisz

4 years ago

@ritesh_panditi I understood it as a class which performs the data transformation and fits to the ml algorithm instead of performing two separate steps and avoids data leakage in the process.

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Datavisz @Datavisz

5 years ago

1.Data cleaning : Outlier detection and removal. 2.Imputing strategies using mean, median, mode 3.Few data transformation techniques 4.Feature importance techniques 5.Xgboost optimization using Optuna Thanks to @dataQueen_pend for the push and collaboration

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Datavisz @Datavisz

5 years ago

Day 110 of #66daysofdata : Made last few submissions for song popularity competition. Not much of an improvement in the score. But I did learn through this completion few techniques on