Dixon Chaudhary's repositories
Machine-Learning
Data Visualization of House Price Prediction, Implementation of Linear Regression, Implementation of Logistic Regression, Data Normalization and Implementation of Perceptron Learning
Computational-Geometry-Lab-Collection-Python
Implementation of Point, Line Segment and Point Line Classification; Implementation of Turn Test; Implementation of Polygon and Ray Casting
AES-Encryption
This project deals about the implementation of AES Algorithm in Java. The project was done during the Seminar organized by Neproid Academy.
awesome-computer-vision
A curated list of awesome computer vision resources
CG-Lab1-C-Sharp
Implementation of Point, Line Segment and checking the position of the point within the line segment
Computational-Geometry-Lab-Collection-Java
Implementation of Point, Line Segment and Point Line Classification; Implementation of Turn Test; Implementation of Polygon and Ray Casting
Cryptography
This project consists of the various Cipher Algorithm which was done in Cryptography subject.
cs230-code-examples
Code examples in pyTorch and Tensorflow for CS230
Digital-Optical-Neural-Network-Code
Relevent code snippets for the digital optical neural network project in Dirk Englund's group
Disaster-Response-Pipelines
Udacity Course Project
Facial-Recognition-Tracking-Computer-Vision-Python
A comparative assessment on facial recognition tracking libraries with computer vision, specifically DLIB and OpenCV's Haar Cascade Classifiers.
feature-engineering-book
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
FlutterTodo
https://dribbble.com/shots/3812962-iPhone-X-Todo-Concept Made With Flutter
Image-OutPainting
🏖 Keras Implementation of Painting outside the box
Lexical-Analyzer
Program to make a simple lexical analyzer of different operators in C
nepali-abstractive-summarization
Abstractive Summarization in the Nepali language
nlp-tutorial
A list of NLP(Natural Language Processing) tutorials
RecommendationsWithIBM
Udacity Data Scientist Nanodegree project.
SMSSpamClassifier-from-NLP-using-RandomForest-and-GradientBoosting-Classifier
Here i simply took SMSSpamClassifier data and using NLTK library along with RandomForest and GradientBoosting Classifier from sklearn.esemble, i classified if that SMS is spam or ham. Firstly, i cleaned raw data removing punctuations, stopwords and tokenizing along with stemming and lemmatizing. Then, moving forward i test vectoring with CountVectorize, N-grams and Tf-Idf vectorizer. And then, moving forward to feature enginnering i add two new features i.e. text length and percentage of punctuations on text.Then evaluate them if it was useful for detecting spam and if transformation was required. Finally it was applied to Gradient Boosting and Random forest classifier along with GridSearch and their performance was evaluated for selecting better hyperparameters using GridSearchCv.
tokenizers
💥Fast State-of-the-Art Tokenizers optimized for Research and Production