muralikrishna26 Goto Github PK
Name: Murali Krishna Kasthala
Type: User
Bio: CS PostGrad, IIIT Delhi
Location: Delhi
Blog: https://www.linkedin.com/in/murali-krishna-kasthala-49141011a/
Name: Murali Krishna Kasthala
Type: User
Bio: CS PostGrad, IIIT Delhi
Location: Delhi
Blog: https://www.linkedin.com/in/murali-krishna-kasthala-49141011a/
In this competitions, one had to develop models using TensorFlow (Python Library) to classify B-cell epitopes and Non-epitope. Developed model is clearly explained in "MT19132_Readme.pdf" file
Diabetes is one of the most commonly known chronic diseases, leading to complications in health if it is unidentified and not diagnosed. Implemented various machine learning algorithms on the data collected from PIMA Indian Diabetes Database, which is sourced from the UCI Machine learning repository. applied machine learning techniques such as K Nearest Neighbors, Logistic regression, Naive Bayes, Decision trees, Gaussian process, Linear SVM, RBF SVM, Xgboost, Gradient boost, AdaBoost and Random forest. All these mentioned algorithms are applied to the normalized data. The performance comparison of the model is discussed based on the accuracy as an evaluation metric, along with a brief description of how every model is implemented in this paper. The voting classifier is applied on top of the best models from the above machine learning techniques listed.
Written a Python program that can take as input any given propositional formula and puts out i) the corresponding truth table, and ii) the corresponding disjunctive normal form of the given formula.
Contains various methods and models that makes retriving of informtion more simplier.
Play with Graphs and Networks
In the present-day technology huge amount of data is being generated every day. So, itβs turning out to be a challenging task to handle text-based data. In the world of text-based sentences it is not that simple to differentiate between fact and opinions. So, This project is to build the model that classifies/identifies facts from/and opinions in the given text by using various machine learning and deep learning techniques.
This system can be used to maintain location of each patient . Information about the patient and the charges to be paid is also stored .
Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation, as these proteins play a crucial role in gene-regulation. We have developed an model using various machine learning techniques to for predicting DNA-binding domains and proteins.
Given DNA Interacting residues, we have created model using various machine learning techniques to predict whether it is protine contained DNA or not.
Classification of high risk and low risk cancer patients using Convolutional Neural Network and Mutli-Layer Perceptron.
RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.
Stage classification of liver cancer patients from thier gene expression profile. Models used are : KNN, Naive Bayes, SVM, LSTM
Created a simple website to conduct a survey on any general issue where both the teachers and students will vote.
Ranking based on Relevance Score. The objective of the project is to predict the relevance score {0, 1, 2} for a given (query, document) pair feature vector in the test set.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. πππ
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.