Product Engineer @ Sprinklr | CSE IIT Ropar

Abhishek Choudhary  • Peerlist

• Here I created a Virtual Blackboard in which people can write on the screen using their Hand gesture and also deployed
it on as a web app locally
• I used the media pipe library of Google to detect the hand of the person in the video
• Used OpenCV library for writing on the board

Virtual Black Board

• Developed a tool in which you can upload the MRI scan of your brain and the tool can predict whether there is a tumor
in the brain or not
• created a flask web API for using it where you can upload the MRI scan to know whether there is a tumor is present or
not.
• Used HTML and CSS to create a front end web page for using it.

Tumor detection

through this I predicted the slae revenue using scikit-learn

Predict Sales Revenue with scikit-learn

1)   Evaluate the performance of a classifier using visual diagnostic tools from Yellowbrick .
2)   Diagnose and handle class imbalance problems

Visual Machine Learning with Yellowbrick 

Through this project I learn 
1) Implement Convolutional Neural Networks in Keras with TensorFlow backend
2) Train Convolutional Neural Networks to solve Image Classification

Image Classification with CNNs using Keras

1)   Solving a multi-class classification problem using the neural network implementation.
2)   Implementation a neural network from scratch using TensorFlow.