Posts from Machine Learning

Optimization Techniques In Neural Network

By Arijit Roychaudhury

In this article, we are going to discuss some of the popular optimization techniques in Neural Network. What is Optimizer in neural network The optimizer is something by virtue of .... Read More

Adam Optimizer in Deep Learning

By Sai Ram

Hey folks, let’s focus on another interesting topic that is, Adam Optimizer in Deep Learning. Before we proceed let’s take an intro. Optimizer Algorithms in Deep Learni.... Read More

Geodemographic segmentation

By Rohit Arodi

In this tutorial, we are gonna see what is Geodemographic segmentation and where do we use is. What is Geodemographic segmentation This can be better explained with an example, sup.... Read More

SVM Parameter Tuning using GridSearchCV in Python

By Prakhar Gupta

In this tutorial, we learn about SVM model, its hyper-parameters, and tuning hyper-parameters using GridSearchCV for precision. Support Vector Machine algorithm is explained with a.... Read More

Semi Supervised Learning (SSL)

By Sai Ram

Hello peeps, let’s get into another interesting topic called semi-supervised learning. According to the data we choose to train there are three types of learning. Supervised Lear.... Read More

How to draw shapes in matplotlib with Python

By Sachin Rastogi

In this article, we are going to learn how to draw different types of basic shapes like Lines, Rectangle, Square, Circle, Triangle in matplotlib using Python. For this, we need som.... Read More

Decision Tree Regression in Python using scikit learn

By Prakhar Gupta

In this tutorial, we are are going to evaluate the performance of a data set through Decision Tree Regression in Python using scikit-learn machine learning library. What is Decisio.... Read More

Anomaly detection in Python using scikit-learn

By Prakhar Gupta

Hello users, this article is for using scikit-learn model for anomaly detection in Python. Introduction to Anomaly Detection Anomaly = Outliers = Unusual Data Point Whenever data g.... Read More

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