ViewTube

Mamba is a new neural network architecture that came out this year, and it performs better than transformers at language ...

In which we discuss an introduction to computational topology, the utility of Betti numbers, simplicial homology (with examples) ...

Lecture 6 in the Introduction to Machine Learning (aka Machine Learning I) course by Dmitry Kobak, Winter Term 2020/21 at the ...

SYDE 522 – Machine Intelligence (Winter 2019, University of Waterloo) Target Audience: Senior Undergraduate Engineering ...

Feature Engineering involves creating new features or modifying existing ones to improve a model's performance, helping capture ...

Deep Learning is a subset of machine learning that involves neural networks with multiple layers (deep neural networks).

This video focuses on providing a clear geometric intuition behind PCA. Learn the basics and set the foundation for understanding ...

In this video, we delve into the world of XGBoost, a powerful and versatile machine learning algorithm. Whether you're a data ...

Get a grasp of Simple Linear Regression in this video that combines both code and intuition. We simplify the concepts and guide ...

Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem ...

This is a comprehensive guide to understanding Gradient Descent. We'll cover the entire process from scratch, providing an ...

In this video, we will start our discussion around CNN. CNNs are one of the most popular neural network architectures. CNNs are ...

Machine Learning Pipelines streamline the end-to-end process of model building, evaluation, and deployment, ensuring a ...

Get familiar with Random Forest in a straightforward way. This video provides an easy-to-understand intuition behind the ...

Exploratory Data Analysis (EDA) through Bivariate and Multivariate Analysis examines relationships between two or more ...

Curious about ROC Curve and ROC-AUC in machine learning but finding it confusing? This video is here to simplify these ...

Imbalanced data refers to datasets where the distribution of classes is heavily skewed, with one class significantly outnumbering ...

Decision Trees use metrics like Entropy and Gini Impurity to make split decisions. Entropy measures the disorder or randomness ...

Understand key metrics for evaluating regression models in this video. We cover Mean Squared Error (MSE), Mean Absolute Error ...

The preliminary analysis of data to discover relationships between measures in the data and to gain an insight on the trends, ...