Name: Akhilesh Ravi
Type: User
Bio: Machine Learning Engineer at Qualcomm
CS and EE graduate from IIT Gandhinagar.
Interested in Machine Learning, Computer Vision and Natural Language Processing
Location: Bangalore, Karnataka, India
Akhilesh Ravi's Projects
Advanced Deep Learning with Keras, published by Packt
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
This repository has codes for converting greyscale images to binary images using various methods in such a way that, to the human eye, they still look a lot like images having various intensity levels.
This repository has a code (function) for K-Nearest Neighbours models. The model is tested on a dataset and compared with the slkearn KNN models. There is runtime analysis and accuracy analysis of the sklearn KNN models for classification and regression.
This repository contains codes and functions for Ridge Regression (Normal Eqquation method and Coordinate Descent method) and Lasso Regression (Coordinate Descent method). There is some analysis of the preformance of these funcions/models. There is also a comparison of these with the sklearn.
This has the Matlab codes for a basic list of morphological functions
This is a repository for Multi-Layer Perceptron and Logistic Regression. There is a code (function) for Logistic Regression. SOme analysis is performed on the function. This is compared with the sklearn Logistic Regression function. Then, the decision boundary has also been plotted for the classification. The next part is the basic neural network. A class and a function has been created for this and it has been used for digit classification (mnist dataset).
This repository has code (function) for Naive Bayes Classifier model which is based on probability. The model is evaluated on a dataset. It has then been used for active learning. Finally, there is a comparison between active learning and adding new samples to the train set from the pool set randomly.
The aim of this repository is to assist in a introductory workshop for OpenCV in Python
This repository has a code for hard SVM. The code is run for the Iris dataset classification. The support vectors are obtained and the decision boundary is drawn. Ultimately, there is a lso a comparison with the sklearn svm framework.
Autonomous Drone to move in a warehouse and make a stock of the inventory be reading the bar codes and QR codes