Aditya Kumar Gupta's Projects
This module can take a list of feature names and the data dictionary, and return a numpy array.
Basic Iris Flower Prediction. Learning how to host ML models using Flask and deploy it using Heroku.
A Person Of Interest identifier based on ENRON CORPUS data.
Write a line of code or create a new file. Let's see where this repo ends up. (Similar to Twitch Plays Pokemon)
Using Multi Layer Perceptron to build the model. Classifies the handwritten digits of the MNIST database with around 98% accuracy.
Using the MNIST dataset which consists of greyscale handwritten digits. Each image is 28x28 pixels. Building and training a neural network that can take one of these images and predict the digit in the image.
GitHub resources and information for the developer community in India
A basic project to implement the KNN classifier from Scratch.
Basic implementation of Lasso, Ridge Regression and Elastic-Net Regularization.
Data Science Bowl Challenge (DSB3)
The Ultimate FREE Machine Learning Study Plan
A basic project to implement Gaussian Naive Bayes.
:cocktail: Open Source Drinks! Add your own recipe in a pull request!
Converts regular RGB images into Pencil-sketch.
A just for fun project.
📷 This repository is focused on having various feature implementation of OpenCV in Python. The aim is to have a minimal implementation of all OpenCV features together, under one roof.
An Encrypted Automatic Multiple-Choice Question Generator for Self-Assessment Using Natural Language Processing
A basic implementation of the Random Forest Classifier from Scratch and using Seaborn to find important features.
A PyPI package that does extractive text summarizer using Cosine Methods in NLTK.
A basic project to build the classification model with SVM (Support Vector Machine)
Basic usage of NLTK. Implementation of concepts like Stemmer, TfIdf, and text.CountVectors
A basic snippet of code that uses Google's gTTS API to convert text to speech. Go on. Play Around with it.
The main task of the character-level language model is to predict the next character given all previous characters in a sequence of data, i.e. generates text character by character.
Training a simple RNN to do time-series prediction. Given some set of input data, it will be able to generate a prediction for the next time step.
Very basic data exploration of the Titanic Dataset.
Welcome to Algo-Phantoms. This is a open source organization which will contribute pathways and resources to start with competitive programming.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent