The Python collections module provides a helpful factory function, namedtuple, which allows you to create named tuples in Python. The idea behind named tuples is to make working with tuples more pythonic by allowing you to access data in the
The mean squared error is a common way to measure the prediction accuracy of a model. In this tutorial, you’ll learn how to calculate the mean squared error in Python. You’ll start off by learning what the mean squared error
In this tutorial, you’ll learn how to combine data in Pandas by merging, joining, and concatenating DataFrames. You’ll learn how to perform database-style merging of DataFrames based on common columns or indices using the merge() function and the .join() method.
In this tutorial, you’ll gain an understanding of what machine learning is and how Python can help you take on machine learning projects. Understanding what machine learning is, allows you to understand and see its pervasiveness. In many cases, people
In this tutorial, you’ll learn what Scikit-Learn is, how it’s used, and what its basic terminology is. While Scikit-learn is just one of several machine learning libraries available in Python, it is one of the best known. The library provides
In this tutorial, you’ll learn how to split your Python dataset using Scikit-Learn’s train_test_split function. You’ll gain a strong understanding of the importance of splitting your data for machine learning to avoid underfitting or overfitting your models. You’ll also learn
In this tutorial, you’ll learn how to learn the fundamentals of linear regression in Scikit-Learn. Throughout this tutorial, you’ll use an insurance dataset to predict the insurance charges that a client will accumulate, based on a number of different factors. You’ll
In this tutorial, you’ll learn what random forests in Scikit-Learn are and how they can be used to classify data. Decision trees can be incredibly helpful and intuitive ways to classify data. However, they can also be prone to overfitting,
In this tutorial, you’ll learn how to dive into the wonderful world of Pandas. Pandas is a Python package that provides fast and flexible data structures used for data manipulation and analysis. By the end of this tutorial, you’ll have
In this tutorial, you’ll learn how to quickly summarize and analyze a Pandas DataFrame. By the end of this tutorial, you’ll have learned to take on some exploratory analysis of your dataset using pandas. You’ll learn how to calculate general
In this tutorial, you’ll learn how to transform your Pandas DataFrame columns using vectorized functions and custom functions using the map and apply methods. By the end of this tutorial, you’ll have a strong understanding of how Pandas applies vectorized
In this tutorial, you’ll learn how to use Python’s NumPy library for data science. You’ll learn why the library matters in the realm of data science and how it’s foundational for many other libraries. You’ll learn about the NumPy ndarray
