Learn about relational operators for comparing R objects and logical operators for combining boolean TRUE and FALSE values. You'll also construct conditional statements. Learn about data types and their importance in a programming language. More specifically, learn how to use various data types like vector, matrices, lists, and dataframes in the R programming language. must read learning data science +5 Wondering whether you should use Python or R for data analysis? You’ve come to the right place. In this tutorial, you'll learn basic time-series concepts and basic methods for forecasting time series data using spreadsheets. Discover Python regular expressions: find basic and complex patterns, repetitions, or to do (non-)greedy matching, work with the re library and much more! Learn the basics of sentiment analysis and how to build a simple sentiment classifier in Python. Learn the common tricks to handle categorical data and preprocess it to build machine learning models! Learn how you can execute a Python script from the command line, and also how you can provide command line arguments to your script. In this basic Python tutorial, you'll learn about why and when you should use inner classes. Learn about the basics of feature selection and how to implement and investigate various feature selection techniques in Python. A tutorial on functions in Python that covers how to write functions, how to call them, and more! Discover Long Short-Term Memory (LSTM) networks in Python and how you can use them to make stock market predictions! Learn about PCA and how it can be leveraged to extract information from the data without any supervision using two popular datasets: Breast Cancer and CIFAR-10. Learn about Markov Chains, their properties, transition matrices, and implement one yourself in Python! In this tutorial, you'll learn about commonly used probability distributions in machine learning literature.