Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were done in Google Colab. Therefore, you should check the ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine ...

Seeing a chance to help the cause, some of the biggest names in AI and machine learning—a discipline within the field—recently published a paper called “Tackling Climate Change with Machine ...

CONTAIN™ represents the next breakthrough in AI-powered ore sorting from TOMRA Mining – a deep learning solution purpose-built to classify complex inclusion-type ores with unprecedented accuracy. By ...

Potential treatments for amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases may already be out there in ...

“Take a weather predictor, for example. The more weather inputs there are, the better the prediction for what will come next.” Whereas machine learning can make predictions, he said artificial ...

Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient ...