Classifier Recall, Explained
Machine learning – and the related field of AI – will probably be worth millions of dollars for people who master these skills. But as I always tell my students:...continue reading.
Machine learning – and the related field of AI – will probably be worth millions of dollars for people who master these skills. But as I always tell my students:...continue reading.
This blog post explains precision in classifiers and machine learning models. It will explain what precision is, the pros and cons of this metric, how to improve precision, and more....continue reading.
Scikit-learn, which is affectionately known as sklearn among Python data scientists, is a Python library that offers a wide range of machine learning tools. Among these tools is the confusion_matrix...continue reading.
This blog post will explain classification accuracy. It will explain what accuracy is, the pros and cons of this metric, how to improve accuracy, and more. Table of Contents: A...continue reading.
When you’re working with classification and detection systems, you’ll commonly hear the term “False Negative.” You might be asking, what is a False Negative? And if you’re a serious machine...continue reading.
Have you ever had someone talk about a classification system or medical diagnostics and mention a “False Positive?” It’s ok … False positives can be confusing if you haven’t worked...continue reading.
If you want to master building classification systems for machine learning, you need to understand how to evaluate classifiers. And in turn, that means you need to understand classification metrics....continue reading.
Data science is now, and will continue to be a hot job. Right now, the average data science salary is somewhere around $150,000. Although many people are claiming that AI...continue reading.
This tutorial will show you how to plot an ROC curve in Python using the Seaborn Objects visualization package. The tutorial is divided into sections for easy navigation, so if...continue reading.
When you begin immersing yourself in the world of classification systems, you’ll encounter a large number of different classification metrics: precision; recall; accuracy; sensitivity and specificity; F1-score; and many more....continue reading.
This tutorial will show you how to use the Scikit Learn roc_curve function. It will explain the syntax of the function and show an example of how to use it....continue reading.
In machine learning, evaluating the performance of a model is as important as its creation. We need tools and techniques to help guarantee that the model performs well and meets...continue reading.
The confusion matrix is an important and commonly used tool in machine learning. This is particularly true of classification problems, where we build systems that predict categorical values. Because they’re...continue reading.
In this tutorial, I’ll show you how to use the Sklearn Logistic Regression function to create logistic regression models in Python. I’ll quickly review what logistic regression is, explain the...continue reading.
With the rise of AI, machine learning has suddenly become very popular. Machine learning has been around for decades, but machine learning systems are becoming increasingly important in a range...continue reading.
The Perceptron stands as one of the most basic building blocks for creating neural networks, including more advanced structures like deep networks and their variants. Originally developed in the late...continue reading.
Unless you’ve been living in cave somewhere in remote Eurasia, you should know that deep learning is very popular, and very powerful. A variety of tools from self driving cars...continue reading.
One of the the questions that I get over and over is, which data science language do I use? I have my own preferences with regards to programming languages, but...continue reading.
Obviously, AI taken off in the last year in ways that were hard for most people to predict. AI went from being a somewhat niche technical subject that nerdy guys...continue reading.
A couple of days ago, I wrote a blog post about how GPT writes bad Pandas code. If you’ve been reading at the blog for a while, you’ve probably realized...continue reading.