Heart Disease Prediction Using Python
Hey fellow coder! Today in this tutorial, we will try to predict the presence of a very common illness in people, heart disease. Heart disease is one of the biggest causes of morbidity and mortality….
Machine Learning
Random Forest in Python
Hello, readers! In this article, we will be focusing on Random Forest in Python, in detail. So, let us begin! 🙂 What is a Random Forest Model? Before diving deep into the construction of a….
Supervised v/s Unsupervised Learning – 4 Key Differences
Hello readers! In our series of Machine Learning concepts, today we will be focusing on Supervised v/s Unsupervised Learning in detail. So, let us begin!! Supervised Machine Learning – Overview In Machine Learning, we come….
Exploratory Data Analysis – Metrics for Measurement
Today, it’s back to basics. We’ll be going over all EDA metrics and which one you should choose – both the when and why.
Regression v/s Classification in Machine Learning
Hey, readers! In this article, we will be focusing on an IMP metric of Machine Learning – Regression v/s Classification, in detail. So, let us begin!! Let us at first discuss about Regression v/s Classification!….
Supervised Machine Learning – A Quick Introduction
Hey, readers! In this article, we will be focusing on one of the main type of Machine Learning Algorithms — Supervised Machine Learning Algorithms. As we all know, Machine Learning is a domain which makes….
Top 11 Machine Learning Datasets for Practice Projects
I decided to compile a list of all the dataset sites and sources I know of.
Face Recognition Technology: Theory of DeepFace and Pyramid CNN
As it was presented in the MIT Technology Review, Facebook’s face recognition article, which was posted and approved on CVPR2014 drew heavy interest. It achieves almost human-like person recognition accuracy by large-scale learning using 4.4….
Genetic Algorithms – A Detailed Introduction
The Genetic Algorithm (GA) is a technique of search-driven optimization based on Genetics and Natural Selection principles.
It is also used to discover optimum or near-optimal solutions to complex situations that would otherwise take a lifetime to solve. It is also used to solve problems of optimization, in science, and in machine learning.
Generative Adversarial Networks – Reinforcement Learning Framework
A type of deep neural network known as the generative adversarial network (GAN) is a subset of deep learning models that produce entirely new images using training data using two of its components.