In this article, we’ll discuss some of the NLP preprocessing techniques while handling the text data. As you have guessed from the title we’ll use spaCy for most of our tasks in this article. So, if you […]
Continue readingMore TagImage 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 […]
Continue readingMore TagIntroduction 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 […]
Continue readingMore TagIntroduction 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 […]
Continue readingMore TagCustom 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 […]
Continue readingMore TagElo 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” […]
Continue readingMore TagPandas Math Functions
In this article we’ll learn some of the commonly used math functions in Pandas. Let’s get started. The abs() function: The first one we are going to see is the abs() function. This function returns the […]
Continue readingMore TagIntroduction 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 […]
Continue readingMore Tag6 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 […]
Continue readingMore TagSimple 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 […]
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