mrgarg/Convolution-Neural-Network

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Created about 5 years ago
Updated about 5 years ago

mrgarg/Convolution-Neural-Network

mrgarg

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Image-Classification

classification of images using support vector machine (python)

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Deepface

A deep learning based project to detect gender,age and emotions of a person

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COVID-19

A small learning project to build a COVID-19 detector using CNN in Keras

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Image-Segmentation

classification of an image into different groups(image segmentation) using KMeans.

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Data-Augmentation

data augmentation is a technique that can be used to artificially expand the size of a training dataset

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Handwritten-Digit-Recognition

handwritten digit recognition on MNIST dataset using k-nearest neighbors algorithm

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Sentiment-Analysis

Analysis of movie reviews with the help of Neural Network.

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Sudoku-WebApp

Sudoku solver practice project build using JavaScript with the help of backtracking

Reinforcement-Learning--CartPole

A Reinforcement Learning Based algorithm(Q-learning) built from scratch to simulate the game 'CartPole-v0' in the OpenAI Gym Environment.

Face-Recognition

face detection and recognition using haarcascades classifier and knn algorithm

git_intro

Deep-Convolution-GANs-DCGANs

Deep convolution GAN on MNIST hand-written dataset using Keras library to generate new fake data.

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Image-Captioning

Image Captioning is the process of generating textual description of an image. It uses both Natural Language Processing and Computer Vision to generate the captions.

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Emoji-Prediction

To predict a suitable emoji for any given sentence.

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Mushroom-Classification

To predict the class of mushrooms with the help of Naive Bayes algorithm, given some features of the mushrooms.

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Music-Generation

generating new music(piano) files by using LSTM with the help of music21 library

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Lyric-Generator-Markov-Chain

probabilistic approach to generate new lyrics using markov chain

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TODO-List

Perceptron

Implementation of Perceptron(smallest neural network) from scratch.

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mrgarg.github.io

My first web page

Diabetes-Classification--Challenge

Classification Task, classify a person as 0 or 1 (Diabetic or Not) using K-Nearest Neighbors classifier

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Multi-Layer-Perceptrons

Three Layer Neural Network architecture created from scratch without using any pre-defined libraries.

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