What tips do you have for completing a good data science capstone project?

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Gaurav Mishra

15 years of experience in online training of Python, R, SAS, SPSS, SQL, Tableau, Data Science and ML

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Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from datain various forms, either structured or unstructured, similar to data mining. To become a data scientist you must have knowledge of - Statistical tools - SAS R Python Statistical techniques - Descriptive statistics Inferential statistic T test, ANOVA, Correlation and Chiesqr technics Factor analysis and cluster analysis Predictive modelling - Leaner regression, Logistic regression, Decision tree. Time series analysis. Machine learning You need good practice, projects and case studies for better understanding of data science concepts. I provide online and classroom training for data science. Thank you Gaurav Mishra | Analytics Foundation read less
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First , Get the right data in for the data frame. conduct extensive data wrangling do exploratory data analysis to understand the data normalise & transform the data chosse right features make a guess on top 3 models to fit in evalute the models fine tune the models to improve the performance...
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First , Get the right data in for the data frame. conduct extensive data wrangling do exploratory data analysis to understand the data normalise & transform the data chosse right features make a guess on top 3 models to fit in evalute the models fine tune the models to improve the performance metrics read less
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Data Scientist

Hi Santosh, From my experience,Following are the tips to complete data science project; 1) Find a well defined problem from your interesting domain(e.g Healthcare,Transportation,Agriculture etc) 2)Collect a data accordingly to your problem. 3) Define Success metric/Evaluation metric for your...
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Hi Santosh, From my experience,Following are the tips to complete data science project; 1) Find a well defined problem from your interesting domain(e.g Healthcare,Transportation,Agriculture etc) 2)Collect a data accordingly to your problem. 3) Define Success metric/Evaluation metric for your problem. 4) Then do some exploratory analysis and buils the model to solve your problem and then evaluate it using defined metric. 5) Present your solution to the community Thanks read less
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