Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn is well-suited for exploring and visualizing multi-dimensional data and can also be used to plot statistical time series data. Some of its key features include a diverse set of pre-built plotting functions, easily readable and concise syntax, and the ability to integrate well with other scientific Python libraries such as NumPy and pandas.
Credit card fraud has become one of the most common use cases for anomaly detection systems. The number of fraud attempts has risen sharply, resulting in billions of dollars in losses. Early detection of fraud attempts with machine learning is therefore becoming increasingly important. In this article, we take on the fight against international credit … Read more
In this tutorial, we’ll be using machine learning to predict and map out crime in San Francisco. We’ll be working with a dataset from Kaggle that contains information on 39 different types of crimes, including everything from vehicle theft to drug offenses. Using Python and the powerful Scikit-Learn library, we’ll train a classification model using … Read more
Are you intrigued by the fascinating world of cryptocurrency and looking to visually decipher its price trends? Welcome aboard! In this comprehensive tutorial, we will explore creating color-coded line charts using Python and Matplotlib, a powerful tool for effective analysis of changes along a third dimension. The past few years have witnessed a meteoric rise … Read more
Customer retention is a prime objective for service companies, and understanding the patterns that lead to customer churn can be the key to maintaining long-lasting client relationships. Businesses incur significant costs when customers discontinue their services, hence it’s vital to identify potential churn risks and take preemptive actions to retain these customers. Machine Learning models … Read more
Are you struggling to find the best hyperparameters for your machine learning model? With Python’s Scikit-learn library, you can use grid search to fine-tune your model and improve its performance. In this article, we’ll guide you through the process of hyperparameter tuning for a classification model, using a random decision forest that predicts the survival … Read more
Are you ready to learn about the exciting world of social media sentiment analysis using Python? In this article, we’ll dive into how companies are leveraging machine learning to extract insights from Twitter comments, and how you can do the same. By comparing two popular classification models – Naive Bayes and Logistic Regression – we’ll … Read more
Online shopping has become a part of our daily lives, and online stores are continually seeking to improve their sales. One way to achieve this is by using machine learning to predict customers’ purchase intentions. This innovative process can help businesses understand their customers’ behavior and tailor their marketing strategies accordingly. In this article, we … Read more
Correlation analysis is a powerful tool in financial market analysis, helping investors to better understand the interdependence of different assets. But what happens when an unprecedented global pandemic like COVID-19 shakes up the market? In this tutorial, we will show you how to create a correlation matrix in Python that will help you visualize the … Read more
