Object Detection from Images with YOLO using Python
Feb 4, 2022
In this tutorial, we're going to show you how to detect objects from images with the YOLO (You Only Look Once) algorithm using Python.
Understanding Enumerate and Zip Functions in Python
Jan 28, 2022
This tutorial shows how to use the Python enumerate function to get indexes of all items in iterables and how to combine iterables using the zip function.
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Adding Interactivity to Jupyter Notebooks with ipywidgets
Jan 14, 2022
In this article, we'll show you how to add interactivity to your Jupyter Notebooks using different interactive widgets from the Python ipywidgets library.
Data Scaling and Normalization in Python with Examples
Dec 17, 2021
Here's how to scale and normalize data using Python. We're going to use the built-in functions from the scikit-learn library and show you lots of examples.
Techniques for Handling Outlier Data with Python
Dec 3, 2021
This article explains what outliers are in datasets and what you can do to handle them in your code. We'll demonstrate several techniques using examples in Python.
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Handwriting Image Classification with Python Sklearn
Nov 26, 2021
In this introduction to image classification, we'll show you how to use Python and sklearn to recognize handwritten numbers in the sklearn load_digits dataset.
Drawing Multiple Plots with Matplotlib in Python
Nov 19, 2021
In this tutorial, we'll show you exactly how to draw multiple plots at once using the Python Matplotlib library. We're going to study both the subplot() and subplots() functions.
Upsampling and Downsampling Imbalanced Data in Python
Nov 12, 2021
Handling imbalanced data in Python is essential. In this tutorial, we'll show you how to balance datasets using two upsampling and one downsampling technique.
Linear Discriminant Analysis with Python scikit-learn
Oct 29, 2021
Here's how to do linear discriminant analysis (LDA) for dimensionality reduction in Python using sklearn. We'll compare our LDA results to PCA, too.
Python PCA Examples with sklearn
Oct 22, 2021
Let's take a look at some examples showing how to use principal component analysis (PCA) for dimensionality reduction with the Python scikit-learn library.
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