Learn about machine learning in Python and build your very first ML model from scratch to predict Airbnb prices using k-nearest neighbors.
Learn data cleaning for a machine learning project by cleaning and preparing loan data from LendingClub for a predictive analytics project.
Learn how to use R functions, including how to use built-in generic functions, how to use vectorization, and how to write your own custom functions.
Learn to do some text analysis in this Python tutorial, and test hypotheses using confidence intervals to insure your conclusions are significant.
Learn text classification using linear regression in Python using the spaCy package in this free machine learning tutorial.
In this beginner Python tutorial, we’ll take a look at mutable and immutable data types, and learn how to keep dictionaries and lists from being modified by our functions.
Poisson Regression can be a really useful tool if you know how and when to use it. In this tutorial we’re going to take a long look at Poisson Regression, what it is, and how R programmers can use it in the real world. Specifically, we’re going to cover:What Poisson Regression actually is and when we […]
Take the first step into image analysis in Python by using k-means clustering to analyze the dominant colors in an image in this free data science tutorial.
In this tutorial, we will learn about the powerful time series tools in the pandas library. Originally developed for financial time series such as daily stock market prices, the robust and flexible data structures in pandas can be applied to time series data in any domain, including business, science, engineering, public health, and many others. […]
In recent weeks, news of the devastating wildfires sweeping parts of the US state of California have featured prominently in the news. While most wildfires are started accidentally by humans, weather conditions like wind and drought can exacerbate fires’ spread and intensity. Improved understanding of historical wildfire trends and causes can inform fire management and […]
Math is like an octopus: it has tentacles that can reach out and touch just about every subject. And while some subjects only get a light brush, others get wrapped up like a clam in the tentacles’ vice-like grip. Data science falls into the latter category. If you want to do data science, you’re going […]
Scikit-learn is a free machine learning library for Python. It features various algorithms like support vector machine, random forests, and k-neighbours, and it also supports Python numerical and scientific libraries like NumPy and SciPy. In this tutorial we will learn to code python and apply Machine Learning with the help of the scikit-learn library, which […]
This post was written by Carolina Bento. She leads Data Analytics teams that empower companies to make data-driven decisions, and currently manages Product Analytics team at eero. This article was originally posted on Medium, and has been reposted with permission. We learn a lot of interesting and useful concepts in school but sometimes it’s not […]
Learn to use Python dictionaries to store, sort, and access data in this in-depth tutorial analyzing craft beer data to master dictionary techniques.
Error metrics are short and useful summaries of the quality of our data. We dive into four common regression metrics and discuss their use cases.