Critical thinking skills must occupy the top shelf of any aspiring data analyst’s arsenal. These include analyzing the data, interpreting, and presenting the data relevant and easily consumable by the reader.
Edward Rolf Tufte, in his book “Beautiful Evidence,” presents us with six principles for giving the data in an informative way.
In his book, Edward Rolf Tufte uses Minard’s map of Russia's French invasion, created in 1869, to beautifully explain all these principles. Interested readers can check this book.
Preprocessing the data is one of the crucial steps of data analysis, one of the preliminary steps in that includes feature scaling. Often, programmers new to data science tend to neglect or bypass the step and directly go to analysing the data; this leads to bias and, in turn, influences the prediction accuracy.
Data Normalization is a data preprocessing step where we adjust the scales of the features to have a standard scale of measure. In Machine Learning, it is also known as Feature scaling.
Machine learning algorithms such as Distance-Based algorithms, Gradient Descent Based Algorithms expect the features to…
Masters’s in Analytics student at RMIT, Australia