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Удаляет лайки, комментарии и прочие данные из вконтакта
PREPARE FOR CERTIFICATION // 96 hours .25 Courses .6 Projects .3 Skill Assessments
Comprehensive data preparation, exploration, visualization, feature engineering, and regression modeling case study: Predict severity level of car accidents in the USA from 2016-2020 using regression models.
PHP-CLI-MATH-TABLE: visualization for help in detect features & cleaning data process in Machine Learning before deep learning. Data engineering. Does not do calcs. Only visualize data in correct format
Pandas kullanarak veri setlerini birleştiren ve tekrar eden verileri temizleyen en sonda da temizlenmiş bir veri seti oluşturan kod.
This repository explores baby names data to come up with interesting insights
Docker container to parse addresses and return coordinates, checking them againts IPEA/IBGE vectorized maps of Brazil
Projects done on data science in python course
Analytics for apps market in Google Play and App Store.
The investors and marketing team of Eniac, an e-commerce tech company, are having discrepancies as to whether it is beneficial to discount products.
For MLSA Workshop
find common skills requested by employers in data science
exploring a database of every LEGO set ever built.
Use Python to perform Data Wrangling (Gathering, Assessing, Cleaning) of the WeRateDogs Twitter account and archive, followed by storing, analyzing and visualizing the wrangled data.
The model predicts the treatment success rate for new TB cases with high accuracy and robustness. Two different approaches: PCA and Bayesian Inference. The Bayesian regression analysis reveals that c_new_sp_tsr and new_sp_fail are significant predictors of the treatment success rate, while other predictors show less certainty in their effects.
Cleaning data using decision tree and k-nn techniques
This is MS Dhoni Dataset, in which I have cleaned the data file. The data has also been added with few filters to know about the performance of MS Dhoni w.r.t opponents and Ground.
M2.951- Tipologia i cicle de vida de les dades (Pràctica 2)
"Data Cleaning in R" lesson from Codecademy
Project Benson, which analyze MTA subway data to predict highest-trafficked stations in New York City, was done in collaboration with Jonathan Sterling (jasterling) and Kelly Jones (kjones5)