Data Science for Fundraising - Ashutosh R Nandeshwar

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Résumé :
Discover the techniques used by the top R programmers to generate data-driven solutions. Although the non-profit industry has advanced using CRMs and donor databases, it has not fully explored the data stored in those databases. Meanwhile, the data scientists, in the for-profit industry, using sophisticated tools, have generated data-driven results and effective solutions for several challenges in their organizations. Wouldn&rsquo...

Biographie:
t you like to learn these data science techniques to solve fundraising problems? After reading Data Science for Fundraising, you can: ? Begin your data science journey with R ? Import data from Excel, text and CSV files, and databases, such as sqllite and Microsoft's SQL Server ? Apply data cleanup techniques to remove unnecessary characters and whitespace ? Manipulate data by removing, renaming, and ordering rows and columns ? Join data frames using dplyr ? Perform Exploratory Data Analysis by creating box-plots, histograms, and Q-Q plots ? Understand effective data visualization principles, best practices, and techniques ? Use the right chart type after understanding the advantages and disadvantages of different chart types ? Create beautiful maps by ZIP code, county, and state ? Overlay maps with your own data ? Create elegant data visualizations, such as heat maps, slopegraphs, and animated charts ? Become a data visualization expert ? Create Recency, Frequency, Monetary (RFM) models ? Build predictive models using machine learning techniques, such as K-nearest neighbor, Naive Bayes, decision trees, random forests, gradient boosting, and neural network ? Build deep learning neural network models using TensorFlow ? Predict next transaction amount using regression and machine learning techniques, such as neural networks and quantile regression ? Segment prospects using clustering and association rule mining ? Scrape data off the web and create beautiful reports from that data ? Predict sentiment using text mining and Twitter data ? Analyze social network data using measures, such as betweenness, centrality, and degrees ? Visualize social networks by building beautiful static and interactive maps ? Learn the industry-transforming trends Regardless of your skill level, you can equip yourself and help your organization succeed with these data science techniques using R....

Sommaire:
t you like to learn these data science techniques to solve fundraising problems? After reading Data Science for Fundraising, you can: ? Begin your data science journey with R ? Import data from Excel, text and CSV files, and databases, such as sqllite and Microsoft's SQL Server ? Apply data cleanup techniques to remove unnecessary characters and whitespace ? Manipulate data by removing, renaming, and ordering rows and columns ? Join data frames using dplyr ? Perform Exploratory Data Analysis by creating box-plots, histograms, and Q-Q plots ? Understand effective data visualization principles, best practices, and techniques ? Use the right chart type after understanding the advantages and disadvantages of different chart types ? Create beautiful maps by ZIP code, county, and state ? Overlay maps with your own data ? Create elegant data visualizations, such as heat maps, slopegraphs, and animated charts ? Become a data visualization expert ? Create Recency, Frequency, Monetary (RFM) models ? Build predictive models using machine learning techniques, such as K-nearest neighbor, Naive Bayes, decision trees, random forests, gradient boosting, and neural network ? Build deep learning neural network models using TensorFlow ? Predict next transaction amount using regression and machine learning techniques, such as neural networks and quantile regression ? Segment prospects using clustering and association rule mining ? Scrape data off the web and create beautiful reports from that data ? Predict sentiment using text mining and Twitter data ? Analyze social network data using measures, such as betweenness, centrality, and degrees ? Visualize social networks by building beautiful static and interactive maps ? Learn the industry-transforming trends Regardless of your skill level, you can equip yourself and help your organization succeed with these data science techniques using R....