Rohit Dwivedi

Rohit Dwivedi

I am currently enrolled in a Post Graduate Program In Artificial Intelligence and Machine learning. Data Science Enthusiast who likes to draw insights from the data. Always amazed with the intelligence of AI. It's really fascinating teaching a machine to see and understand images. Also, the interest gets doubled when the machine can tell you what it just saw. This is where I say I am highly interested in Computer Vision and Natural Language Processing. I love exploring different use cases that can be build with the power of AI. I am the person who first develops something and then explains it to the whole community with my writings.
image data augmentation

How Data Augmentation Impacts Performance Of Image Classification, With Codes

The article demonstrates how to do data augmentation to increase the size of the data. We will first build a deep learning model without performing augmentation and will compute the accuracy. After which we will build a similar deep learning model after performing augmentation and compute the accuracy. Finally, we will compare the performance of both models.

Beginners Guide to Pycharm IDE

Pycharm IDE For Dummies- Beginners Guide

This article will demonstrate everything you need to know before writing your first code in Pycharm IDE. The article will take you from installing the software and dependencies to writing your first code in Pycharm followed by a classification problem on iris data set where we will classify which class does the flower belong to.

Machine Learning Model Deployment

Hands-On-Guide To Machine Learning Model Deployment Using Flask

The article demonstrates how to deploy a model in real-time using Flask and Rest API through which we would be able to make predictions for the incoming data. We will build a classification model for classifying wine and will deploy it to make real-time class predictions.

Capsule Net

Understanding Capsule Networks with Its Implementation in Computer Vision

This article illustrates the problems with standard neural net and implementation of Capsule Network to overcome the problems. We will first go through the need for such a network and then will implement the CapsNet model in the task of image reconstruction where we will use the MNIST handwritten digit dataset.

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