Learn the basics of sentiment analysis and how to build a simple sentiment classifier in Python. In this tutorial, the reader will learn the Monte Carlo methodology and its applications in data science, like integral approximation, and parameter estimation. In this tutorial, you'll learn how to use JSON in Python. Learn what formulates a regression problem and how a linear regression algorithm works in Python. In this tutorial, you'll learn how to integrate MongoDB with your Python applications. In this tutorial, you'll learn to join multiple datasets in R. In this tutorial, you're going to learn about the uses of underscore(_) in python. Learn to how to create a simple API from a machine learning model in Python using Flask. In this tutorial, you will use geospatial data to plot the path of Hurricane Florence from August 30th to September 18th. This tutorial covers the introduction to Stemming & Lemmatization used in Text and Natural Language Processing. In this tutorial, you'll learn about commonly used probability distributions in machine learning literature. Practice autocorrelation in R by using course material from DataCamp's Introduction to Time Series Analysis course. Practice basic programming skills in R by using course material from DataCamp's free Model a Quantitative Trading Strategy in R course. Learn Time Series Analysis with R along with using a package in R for forecasting to fit the real-time series to match the optimal model. In this tutorial, you are going to learn how to create GUI apps in Python. You'll also learn about all the elements needed to develop GUI apps in Python.