Python is one of the most widely used programming languages. It’s getting a lot of popularity these days because of so many Python frameworks in IoT, Machine Learning, Deep Learning, and Artificial Intelligent space.
These Python Tutorials will help you in getting mastery over the Python Programming. The tips and tricks shared by us will enable you to write pythonic code with high performance, reusability, readability, and maintainability.
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…
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Tensorflow is one of the most popular and widely used software applications in the world. Developers use it to create and implement deep learning algorithms. Even though it is popular for being easy to use, sometimes users might face difficulty…
Non-parametric statistics do not assume any strong assumptions of the distribution, which contrasts with parametric statistics. Non-parametric statistics focus on ranks and signs along with minimal assumptions. Non-parametric statistics focus on analyzing data without making strong assumptions about the underlying…
Maximum a posteriori ( MAP ) is an estimation technique that estimates the most probable value ( mode ) of an unknown quantity of some data. In this article, we calculate MAP using the combination of prior distribution and likelihood…
McNemar’s test is a statistical method used to compare paired categorical data with two categories, often used to evaluate the effectiveness of a treatment or intervention. It involves creating a 2×2 contingency table, calculating the test statistic, and comparing it…
As with any software or programming language, they evolve and the older versions reach the end of their support life cycle. The developer team no longer wants to update older versions when newer ones appear. The team only wants to…