Supervised and unsupervised learning are two different common types of machine learning tasks that are used to solve many different…
In machine learning, prediction and inference are two different concepts. Prediction is the process of using a model to make…
Are you interested in using neural networks to solve complex regression problems, but not sure where to start? Sklearn's MLPRegressor…
Are you preparing for a job interview in the field of deep learning or neural networks? If so, you're likely…
Machine learning has become a fundamental part of almost every industry today. With the increasing demand for data scientists and…
Lung diseases, including chronic obstructive pulmonary disease (COPD), are a leading cause of death worldwide. Early detection and treatment are…
If you're building machine learning models for solving different prediction problems, you've probably heard of clustering. Clustering is a popular…
Preparing for a job interview can be a nerve-wracking experience. It's natural to feel a sense of pressure as you…
Eigenvalues and eigenvectors are important concepts in linear algebra that have numerous applications in data science. They provide a way…
Amazon Web Services (AWS) has announced the launch of Amazon Bedrock and Amazon Titan foundational models (FMs), making it easier…
Artificial Neural Networks (ANN) are a powerful machine learning / deep learning technique inspired by the workings of the human…
Support vector machines (SVM) are a popular and powerful machine learning technique for classification and regression tasks. SVM models are…
Meta Researchers have, yesterday, unveiled a groundbreaking new model, namely Segment Anything Model (SAM), alongside an immense dataset, the Segment…
In the world of generative AI models, autoencoders (AE) and variational autoencoders (VAEs) have emerged as powerful unsupervised learning techniques…
As a data scientist, understanding the nuances of various loss functions is critical for building effective machine learning models. Choosing…
When diagnosing diseases that require X-rays and image-based scans, such as cancer, one of the most important steps is analyzing…