For Python developers, the Levenshtein distance package is one of the most valuable tools for text analysis, comparison, and natural language processing. The Levenshtein distance algorithm is indispensable because it is used in many real-life applications such as bioinformatics, speech…
Optimizing Machine Learning Models with Random Search Hyperparameter Tuning. The random search is a hyperparameter optimization technique. This is considered the best alternative to grid search. In this article, we are going to study the concept of random search in…
If you have ever coded in any programming language, you may understand the importance of great code quality and correctness. CheckStyle is a Java tool that helps discover potential issues and maintain code standards. Similarly in Python, Flake8 can be…
Delivery route planning is one of the most important aspects that helps minimize drivers’ delivery cost and travel time. Popular techniques like Just in Time ( JIT ) and lean management depend tremendously on Delivery route planning. Delivery route optimization…
The Capital Asset Pricing Model ( CAPM ) is a fundamental concept in finance that gives us the expected return on investment, considering its risk and the overall market’s behavior. It is an important part of modern portfolio theory and…
Computer vision tasks are responsible for making computers see the world as we do, through our eyes, and perceive the information similarly. There are many computer-vision tasks such as object detection, object/image recognition, object segmentation, optical character recognition(OCR), pose estimation,…
Exception handling is a very important part of Python code. Python programming language alerts the programmer of any unexpected situations, this is known as an exception. Sometimes, there are situations where exceptions go unnoticed and the interpreter provides us a…
Empirical distribution in Python describes the distribution of data from what is observed rather than having an underlying assumption. It represents the frequency or proportion of observations falling into a particular range by using histograms, cumulative distribution functions (CDFs), or…
Optimization is one of the most fundamental functions of any algorithm. Unconstrained optimization problems refer to those problems where we need to maximize or minimize our function without any constraint on our decision variables. These problems find their usage in…
It has become the need of the hour to use machine learning models and neural networks to detect fraud. The availability of modern technology has enabled us to detect scams without having to identify and scrutinize everything manually. In the…