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

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

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

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 ...

See https://uvaml1.github.io for annotated slides and a week-by-week overview of the course. This work is licensed under a ...

Take my Full Databricks Course Here: https://www.analystbuilder.com/courses/modern-data-workflows-in-databricks In this video ...

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 ...

Specially my target audience are only students, professional who eager to learn Current Technology in IT Industry.

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 ...

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

Let's talk about Boltzmann Machines RESOURCES [1 ] Main paper: ...

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 ...

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

Notes - https://drive.google.com/file/d/1AGcGb49pU55Dm2B7aBRBgaTKMNrBIXm6/view?usp=sharing ML project link ...

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