Getting into Machine Learning and AI is not an easy task. Many aspiring professionals and enthusiasts find it hard to establish a proper path into the field, given the enormous amount of resources available today. The field is evolving constantly and it is crucial that we keep up with the pace of this rapid development. […]
Category: Libraries
Articles about Python libraries
Basic Statistics in Python: Probability
When studying statistics, you will inevitably have to learn about probability. It is easy lose yourself in the formulas and theory behind probability, but it has essential uses in both working and daily life. We’ve previously discussed some basic concepts in descriptive statistics; now we’ll explore how statistics relates to probability. Prerequisites: Similar to the […]
Generating Random Data in Python (Guide)
How random is random? This is a weird question to ask, but it is one of paramount importance in cases where information security is concerned. Whenever you’re generating random data, strings, or numbers in Python, it’s a good idea to have at least a rough idea of how that data was generated. Here, you’ll cover […]
A Basic Pandas Dataframe Tutorial for Beginners
In this Pandas tutorial we will learn how to work with Pandas dataframes. More specifically, we will learn how to read and write Excel (i.e., xlsx) and CSV files using Pandas. We will also learn how to add a column to Pandas dataframe object, and how to remove a column. Finally, we will also learn […]
Basic Statistics in Python: Descriptive Statistics
The field of statistics is often misunderstood, but it plays an essential role in our everyday lives. Statistics, done correctly, allows us to extract knowledge from the vague, complex, and difficult real world. Wielded incorrectly, statistics can be used to harm and mislead. A clear understanding of statistics and the meanings of various statistical measures […]
Python Histogram Plotting: NumPy, Matplotlib, Pandas & Seaborn
In this tutorial, you’ll be equipped to make production-quality, presentation-ready Python histogram plots with a range of choices and features. If you have introductory to intermediate knowledge in Python and statistics, you can use this article as a one-stop shop for building and plotting histograms in Python using libraries from its scientific stack, including NumPy, […]
The Ultimate List of Python YouTube Channels
We couldn’t find a good, up-to-date list of Python developer or Python programming YouTube channels online. Learning Python on YouTube is a viable option these days, and we’re excited about what this new medium can do for programming education. There are some really good YouTube channels that focus on Python development out there, but we […]
Generating Climate Temperature Spirals in Python
Ed Hawkins, a climate scientist, tweeted the following animated visualization in 2017 and captivated the world: This visualization shows the deviations from the average temperature between 1850 and 1900. It was reshared millions of times over Twitter and Facebook and a version of it was even shown at the opening ceremony for the Rio Olympics. […]
Pure Python vs NumPy vs TensorFlow Performance Comparison
Python has a design philosophy that stresses allowing programmers to express concepts readably and in fewer lines of code. This philosophy makes the language suitable for a diverse set of use cases: simple scripts for web, large web applications (like YouTube), scripting language for other platforms (like Blender and Autodesk’s Maya), and scientific applications in […]
Regression of a Proportion in Python
I frequently predict proportions (e.g., proportion of year during which a customer is active). This is a regression task because the dependent variables is a float, but the dependent variable is bound between the 0 and 1. Googling around, I had a hard time finding the a good way to model this situation, so I’ve […]
Pipenv: A Guide to the New Python Packaging Tool
Pipenv is a packaging tool for Python that solves some common problems associated with the typical workflow using pip, virtualenv, and the good old requirements.txt. In addition to addressing some common issues, it consolidates and simplifies the development process to a single command line tool. This guide will go over what problems Pipenv solves and […]
Look Ma, No For-Loops: Array Programming With NumPy
It is sometimes said that Python, compared to low-level languages such as C++, improves development time at the expense of runtime. Fortunately, there are a handful of ways to speed up operation runtime in Python without sacrificing ease of use. One option suited for fast numerical operations is NumPy, which deservedly bills itself as the […]
Jupyter Notebook for Beginners: A Tutorial
The Jupyter Notebook is an incredibly powerful tool for interactively developing and presenting data science projects. A notebook integrates code and its output into a single document that combines visualisations, narrative text, mathematical equations, and other rich media. The intuitive workflow promotes iterative and rapid development, making notebooks an increasingly popular choice at the heart […]
Pythonic Data Cleaning With NumPy and Pandas
Data scientists spend a large amount of their time cleaning datasets and getting them down to a form with which they can work. In fact, a lot of data scientists argue that the initial steps of obtaining and cleaning data constitute 80% of the job. Therefore, if you are just stepping into this field or […]
Exploring ROC Curves
I’ve always found ROC curves a little confusing. Particularly when it comes to ROC curves with imbalanced classes. This blog post is an exploration into receiver operating characteristic (i.e. ROC) curves and how they react to imbalanced classes. I start by loading the necessary libraries. 1 2 3 4 import numpy as np import matplotlib.pyplot […]