哪些数据科学技能最重要?

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by Matt Dancho

Plan	Skills
Machine Learning	Supervised Classification, Supervised Regression, Unsupervised Clustering, Dimensionality Reduction, Local Interpretable Model Explanation-H2OAutomatic Machine Learningparsnip(XGBoostSVM, Random ForestGLM), K-Means, UMAP, recipes, lime
Data Visualization	Interactive and Static Visualizations, ggplot2 and plotly
Data Wrangling & Cleaning	Working with outliers, missing data, reshaping data, aggregation, filtering, selecting, calculating, and many more critical operations dplyr and tidyr packages
Data Preprocessing& Feature Engineering	Preparing data for machine learning, Engineering Features(dates, text, aggregates), Recipes package
Time Series	Working with date/datetime data, aggregating transforming, visualizing time series, timetk package
Forecasting	ARIMA, Exponential Smoothing, Prophet, Machine Learning(XGBoostRandom Forest GLMnet, etc), Deep Learning(GluonTS), Ensembles, Hyperparameter Tuning, Scaling to1000s of forecasts, Modeltime package
Text	Working with text data, Stringr
NLP	Machine learning, Text Features
Functional	Progamming Making reusable functions, sourcing code
Iteration	Loops and Mapping, using Purrr package
Reporting	Rmarkdown, Interactive HTML, Static PDF
Applications	Building Shiny web applications, Flexdashboard
Deployment	Cloud(AWSAzureGCP)Docker, Git
Databases	SQL(for data import), MongoLs(for apps)

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