8 COMMON MISTAKES MADE IN DATA SCIENCE/STATISTICAL MODELLING
240 بار بازدید -
9 ماه پیش
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#datascience
#datascience #statistics #machinelearning #AI
Here I discuss about some of the common mistake made by people in data science modelling.
1- not defining the problem statement well
2- Sample is not representative
3- Misuse of p-value
4-Lack of proper data quality checks
5- Improper model validation/cross validation
6- Not checking if model assumptions are valid
7- Not having a proper monitoring strategy
I have made a beginner friendly (yet detailed) course on Quant Finance. For my course on Quantitative Finance contact [email protected] or WhatsApp me on +31 625521289 or +91 9811519397 (do not call, just drop me a message on WhatsApp).
Join this channel to get access to perks:
@analyticsuniversity
#finance #machinelearning #datascience
For courses on Credit risk modelling, Market Risk Analytics, Marketing Analytics, Supply chain Analytics and Data Science/ML projects contact [email protected]
For Study Packs : http://analyticuniversity.com/
Coursera : https://imp.i384100.net/LXKv2V
DataCamp: https://datacamp.pxf.io/5gbx6b
Skillshare: https://skillshare.eqcm.net/LLDEY
Coursera :
Data Science : http://bit.ly/37nABr6
Data Science Python : http://bit.ly/2ZK5oMm
Recommended Data Science Books on Amazon :
Python for Data Science: https://geni.us/PythonDataScience
R for Data Science : https://geni.us/DataScienceR
Machine Learning using Tensorflow: https://geni.us/MLinTensorflow
Data Science from Scratch: https://geni.us/DataSciencefromScratch
Python programming: https://geni.us/LearnPython
Artificial Inteligence: https://geni.us/LearnAI
Data Vizualization : https://geni.us/DataViz
Here I discuss about some of the common mistake made by people in data science modelling.
1- not defining the problem statement well
2- Sample is not representative
3- Misuse of p-value
4-Lack of proper data quality checks
5- Improper model validation/cross validation
6- Not checking if model assumptions are valid
7- Not having a proper monitoring strategy
I have made a beginner friendly (yet detailed) course on Quant Finance. For my course on Quantitative Finance contact [email protected] or WhatsApp me on +31 625521289 or +91 9811519397 (do not call, just drop me a message on WhatsApp).
Join this channel to get access to perks:
@analyticsuniversity
#finance #machinelearning #datascience
For courses on Credit risk modelling, Market Risk Analytics, Marketing Analytics, Supply chain Analytics and Data Science/ML projects contact [email protected]
For Study Packs : http://analyticuniversity.com/
Coursera : https://imp.i384100.net/LXKv2V
DataCamp: https://datacamp.pxf.io/5gbx6b
Skillshare: https://skillshare.eqcm.net/LLDEY
Coursera :
Data Science : http://bit.ly/37nABr6
Data Science Python : http://bit.ly/2ZK5oMm
Recommended Data Science Books on Amazon :
Python for Data Science: https://geni.us/PythonDataScience
R for Data Science : https://geni.us/DataScienceR
Machine Learning using Tensorflow: https://geni.us/MLinTensorflow
Data Science from Scratch: https://geni.us/DataSciencefromScratch
Python programming: https://geni.us/LearnPython
Artificial Inteligence: https://geni.us/LearnAI
Data Vizualization : https://geni.us/DataViz
9 ماه پیش
در تاریخ 1402/09/12 منتشر شده
است.
240
بـار بازدید شده