Math in Data Science
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 […]
Read MoreScikit-learn Tutorial: Machine Learning in Python
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 […]
Read MoreLinear Regression in Real Life
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 perlesson. We learn a lot of interesting and useful concepts in school but sometimes it’s not […]
Read MorePython Dictionary Tutorial: Analyze Craft Beer with Dictionaries
Learn to use Python dictionaries to store, sort, and access data in this in-depth tutorial analyzing craft beer data to master dictionary techniques.
Read MoreTutorial: Understanding Regression Error Metrics in Python
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.
Read MoreTutorial: Basic Statistics in Python — Probability
Explore statistics for data science by learning probability is, normal distributions, and the z-score — all within the context of analyzing wine data.
Read MoreTutorial: Basic Statistics in Python — Descriptive Statistics
Learn how to do descriptive statistics in Python with this in-depth tutorial that covers the basics (mean, median, and mode) and more advanced topics.
Read More12 Essential Command Line Tools for Data Scientists
Learn 12 useful command line/terminal commands for data science work.
Read MorePython Generators
Python generators are a powerful, but misunderstood tool. They’re often treated as too difficult a concept for beginning programmers to learn — creating the illusion that beginners should hold off on learning generators until they are ready. I think this assessment is unfair, and that you can use generators sooner than you think. In this […]
Read MoreProgramming Best Practices For Data Science
The data science life cycle is generally comprised of the following components: data retrieval data cleaning data exploration and visualization statistical or predictive modeling While these components are helpful for understanding the different phases, they don’t help us think about our programming workflow. Often, the entire data science life cycle ends up as an arbitrary […]
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