(testing signal)

Tag: frauddetection

Best Data Science Certifications In 2022

Over a span of the recent few years, data science has become an integral part of all the major industry sectors, ranging from agriculture, marketing analytics, public policy, to fraud detection, risk management, and marketing optimization. One of the goals of data science is to resolve the many issues that preside within the economy at large, and its other branches and individual sectors, through the use of machine learning, predictive modeling, statistics, and data preparation.

Data science emphasizes the utilization of the general methods but without changing its application, no matter what its domain is. In this way, this approach is a lot more different from the other traditional statistics scenario that usually tends to focus solely upon seeking specific solutions to particular domains or sectors.


Mastering Outlier Detection in Python

Outlier detection, also known as anomaly detection, is a common task for many data science teams. It is the process of identifying data points that have extreme values compared to the rest of the distribution. Outlier detection has a wide range of applications including data quality monitoring, identifying price arbitrage in finance, detecting cybersecurity attacks, healthcare fraud detection, banknote counterfeit detection and more.

In each of these applications, outliers correspond to events that are rare or uncommon. For example, in the case of cybersecurity attacks, most of the events represented in the data will not reflect an actual attack.


A guide to XGBoost hyperparameters

What is the one machine learning algorithm — if you ask — that consistently gives superior performance in regression and classification?

XGBoost it is. It is arguably the most powerful algorithm and is increasingly being used in all industries and in all problem domains —from customer analytics and sales prediction to fraud detection and credit approval and more.

It is also a winning algorithm in many machine learning competitions. In fact, XGBoost was used in 17 out of 29 data science competitions on the Kaggle platform.

Not just in businesses and competitions, XGBoost has been used in scientific experiments such as the Large Hadron Collider (the Higgs Boson machine learning challenge).


Credit Card Fraud Detection Using Machine Learning & Python

As we are moving towards the digital world — cybersecurity is becoming a crucial part of our life. When we talk about security in digital life then the main challenge is to find the abnormal activity.

When we make any transaction while purchasing any product online — a good amount of people prefer credit cards. The credit limit in credit cards sometimes helps us me making purchases even if we don’t have the amount at that time. but, on the other hand, these features are misused by cyber attackers.

To tackle this problem we need a system that can abort the transaction if it finds fishy.