AI ASPIRANT - Learn How Machines Learn

Image Segmentation: Brain MRI Segmentation

In this article we’ll see how to perform Brain tumor segmentation from MRI images. We’ll try different architectures which are popular for image segmentation problems. Let’s start off by defining what our business problem is. Business […]

Introduction to Neural Networks Part – 2

In the Part 1 of Introduction to Neural Networks we learned about one of the simplest artificial neuron called McCulloch-Pitts neuron and implemented it in python. The problem with M-P neuron is that there is actually […]

Introduction to Neural Networks – Part 1

A neural network is an algorithm whose design was inspired by the functioning of the human brain. It tries to emulate the basic functions of the brain. Due to the intentional design of ANNs as conceptual […]

Custom Callbacks in Keras

Keras comes with a long list of predefined callbacks that are ready to use. Keras callbacks are functions that are executed during the training process. According to Keras Documentation, A callback is a set of functions […]

Elo Merchant Category Recommendation – Kaggle Competition

Table Of Contents: 1) Business Problem 2) Data description 3) Exploratory Data Analysis 4) Data preparation/Feature engineering 5) Model Building 6) Submit model on Kaggle 1. Business Problem 1.1) Problem Description: Elo Merchant Category Recommendation” […]

Introduction to Decision Trees

Decision trees are one of the most powerful and widely used supervised models that can either perform regression or classification. In this tutorial, we’ll concentrate only on the classification setting. A decision tree consists of rules […]

6 Regularization Techniques for Deep Learning

One of the most common problems of training a deep neural network is that it overfits. Overfitting occurs when the network learns specific patterns in the training data and is unable to generalize well over new […]

Simple Linear Regression using Keras

Regression is a statistical approach used for predicting real values like age, weight, salary, for example. In regression, we have a dependent variable which we want to predict using some independent variables. The goal of regression […]

KNN from Scratch

The K-Nearest Neighbor(KNN) classifier is one of the easiest classification methods to understand and is one of the most basic classification models available. KNN is a non-parametric method which classifies based on the distance to the […]

Singular Value Decomposition for Dimensionality Reduction

Singular Value Decomposition usually referred to as SVD, is a type of matrix decomposition technique that is popularly used to reduce the dimensions of the data. SVD decomposes a mxn real matrix A into a product […]

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