priyatransbit

-Fake-News-Detection-

Fake news is misinformation or manipulated news that is spread across the social media with an intention to damage a person, agency and organisation. Due to the dissemination of fake news, there is a need for computational methods to detect them. Fake news detection aims to help users to expose varieties of fabricated news. To achieve this goal, first we have taken the datasets which contains both fake and real news and conducted various experiments to organize fake news detector. We used natural processing, machine learning and deep learning techniques to classify the datasets. We yielded a comprehensive audit of detecting fake news by including fake news categorization, existing algorithms from machine learning techniques. In this project, we explored different machine learning models like Naïve Bayes, K nearest neighbors, decision tree, random forest and deep learning networks like Shallow Convolutional Neural Networks (CNN), Deep Convolutional Neural Network (VDCNN), Long Short-Term Memory Network (LSTM), Gated Recurrent Unit Network (GRU), Combination of Convolutional Neural Network with Long Short-Term Memory (CNN-LSTM) and Convolutional Neural Network with Gated Recurrent Unit (CNN-LSTM).

Cookbook

The Data Engineering Cookbook

design-patterns

ebooks_pdfs

FAANG-Coding-Interview-Questions

A curated List of Coding Questions Asked in FAANG Interviews

Fake-News-Detection

Let's hunt Fake News using Word2Vec, GloVe, FastText or learnt from corpus German embeddings.

Fake-News-Detection-1

Fake News Detection using LSTM, CNN

Fake-News-Detection-2

Fakeddit

r/Fakeddit New Multimodal Benchmark Dataset for Fine-grained Fake News Detection

FakeNewsNet

This is a dataset for fake news detection research

FinalDissertation

BITS PILANI Dissertation

Keyist-Ecommerce

🔑 A simple ecommerce site powered with Spring Boot + Angular 10 + Ngrx + OAuth2

Leetcode_company_frequency

Collection of leetcode company tag problems. Periodically updating.

LLD

Curated Collection of all Low level design Questions and implementation asked in major Tech companies , Get yourself prepared for the LLD round and ace the interview.

machine-learning-systems-design

A booklet on machine learning systems design with exercises

Mastering-Big-Data-Analytics-with-PySpark

Mastering Big Data Analytics with PySpark, Published by Packt

matchingMarkets

Analysis of Stable Matchings in R ::

microservices-examples

Examples of microservices

MLWithPytorch

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

nlpia

Examples and libraries for "Natural Language Processing in Action" book

notebooks

pcf-crash-course-with-spring-boot

PCF Crash Course for Java, Spring and Spring Boot Developers - Deploy Spring Boot REST API, Full Stack Applications and Microservices to Pivotal Cloud Foundry (PCF)

spark-1

Apache Spark - A unified analytics engine for large-scale data processing

spring-boot-microservices

Spring Boot Template for Micro services Architecture - Show cases how to use Zuul for API Gateway, Spring OAuth 2.0 as Auth Server, Multiple Resource (Web Services) Servers, Angular Web App, Eureka dor registration and Discover and Hystrix for circuit breaker

spring-boot-microservices-series

Code for SpringBoot MicroServices Blog Series

spring-petclinic-microservices

Distributed version of Spring Petclinic built with Spring Cloud

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

UberClone

React Native Uber Mobile App

what-happens-when

An attempt to answer the age old interview question "What happens when you type google.com into your browser and press enter?"