398 skills found · Page 4 of 14
lordtao / Android Tao Rest Data ProcessorAndroid REST Data Processor library. Easy to build a REST request, to receive and processing data (XML, JSON, CSV and etc.) from REST requests, file system, assets. This project is no longer actively maintained.
TowsifAhamed / C Project Using Object Oriented Programming For Booking Hotel Room Restaurant And Convention HallA c++ project which can create and search for client id and book hotel room, restaurant & convention hall and also calculates the cost. Here Object Oriented Programming has been used along with the examples of file management including csv files, polymorphism, diamond problem, constructor, operator overloading, virtual class, exception handling and so on. The project is well documented to learn.
vkgnandhu177 / Bayesian Regression And Bitcoin# Bayesian-Regression-to-Predict-Bitcoin-Price-Variations Predicting the price variations of bitcoin, a virtual cryptographic currency. These predictions could be used as the foundation of a bitcoin trading strategy. To make these predictions, we will have to familiarize ourself with a machine learning technique, Bayesian Regression, and implement this technique in Python. # Datasets We have the datasets in the data folder. The original raw data can be found here: http://api.bitcoincharts.com/v1/csv/. The datasets from this site have three attributes: (1) time in epoch, (2) price in USD per bitcoin, and (3) bitcoin amount in a transaction (buy/sell). However, only the first two attributes are relevant to this project. To make the data to have evenly space records, we took all the records within a 20 second window and replaced it by a single record as the average of all the transaction prices in that window. Not every 20 second window had a record; therefore those missing entries were filled using the prices of the previous 20 observations and assuming a Gaussian distribution. The raw data that has been cleaned is given in the file dataset.csv Finally, as discussed in the paper, the data was divided into a total of 9 different datasets. The whole dataset is partitioned into three equally sized (50 price variations in each) subsets: train1, train2, and test. The train sets are used for training a linear model, while the test set is for evaluation of the model. There are three csv files associated with each subset of data: *_90.csv, *_180.csv, and *_360.csv. In _90.csv, for example, each line represents a vector of length 90 where the elements are 30 minute worth of bitcoin price variations (since we have 20 second intervals) and a price variation in the 91st column. Similarly, the *_180.csv represents 60 minutes of prices and *_360.csv represents 120 minutes of prices. # Project Requirements We are expected to implement the Bayesian Regression model to predict the future price variation of bitcoin as described in the reference paper. The main parts to focus on are Equation 6 and the Predicting Price Change section. # Logic in bitcoin.py 1. Compute the price variations (Δp1, Δp2, and Δp3) for train2 using train1 as input to the Bayesian Regression equation (Equations 6). Make sure to use the similarity metric (Equation 9) in place of the Euclidean distance in Bayesian Regression (Equation 6). 2. Compute the linear regression parameters (w0, w1, w2, w3) by finding the best linear fit (Equation 8). Here you will need to use the ols function of statsmodels.formula.api. Your model should be fit using Δp1, Δp2, and Δp3 as the covariates. Note: the bitcoin order book data was not available, so you do not have to worry about the rw4 term. 3. Use the linear regression model computed in Step 2 and Bayesian Regression estimates, to predict the price variations for the test dataset. Bayesian Regression estimates for test dataset are computed in the same way as they are computed for train2 dataset – using train1 as an input. 4. Once the price variations are predicted, compute the mean squared error (MSE) for the test dataset (the test dataset has 50 vectors => 50 predictions).
rajtoshranjan / Automatic Certificate Generator And Sender Website Using DjangoThe certificate generation and sending system in python is flexible for generating the certificate of the students who participate or attend the different workshops, webinars, quiz, live project, etc. The system is targeted at various enterprises, schools, colleges, and universities. The development of system focuses at describing the tables with columns/rows & sub-columns, sub-rows, rules of data selection for calculating credits and grades of the students & summarizing exam data, particular table, column/row, and formatting the data in the destination document. Certificate generation and sending system can be used in universities, colleges, schools, enterprises to automate the distribution of certificates digitally. The system access information of participants from the CSV which is uploaded by the user and generates & send the certificate of all the participants in a portable document format which provides authenticity of the document on their respective email id. The Certificate generation and sending system is a system which allows the digital automation of the certificate of the students. The system will generate the certificate in Portable Document Format which is globally accepted format for files. The PDF document is very difficult to modify and requires the use of the complex software.
LaravelDaily / Laravel Import CSV Chart.js ReportsLaravel project demo for importing CSV and generating Chart.js reports - generated with QuickAdminPanel
MehdiTAZI / BitCoinAccountsBlanceCheckerthe project generates a csv file with private and public keys with it corresponding current balance from the main bitcoin blockchain.
LohithArcot / Easy RasaPython package for Rasa deployed on official repo pypi.org. https://pypi.org/project/easy-rasa/ Converts data present in a standard format in CSV to rasa format nlu.md file
alsonpr / Henley Passport Index DatasetThis is a Python project that utilizes an API provided by the Henley Passport Index and converts the collected information into a structured CSV format.
autodesk-platform-services / Aps Hubs Recursive ExtractionFiles and folders extraction sample:Sample to demonstrate how to retrieve data of all the folders and files on a specific project to show on a table and export it as CSV.
ignatandrei / Export Word Excel PDF CSV HTMLthis project shows how to export to word / excel / pdf / csv / html
projectcsv / Projectcsv.github.ioProject CSV - Website / Web App for opening, viewing, and editing .csv files online or offline.
sergueik / Testng DataprovidersThis project exercises TestNG data providers: Excel 2003, 2007, Open Office, JSON, csv, Fillo
minuteoflaravel / Laravel Csv ValidatorAdds CSV validator to your Laravel project
MThoma202 / Prosper 1099 ParserProject to convert PDF files containing Prosper 1099-B transactions to CSV format.
ShuaiBOnlyLoveEating / Nomoto PID Trajectory TrackingBased on the first-order Nomoto model and an improved PID controller, the project realizes real-time tracking control and visualization of a given trajectory (CSV historical point column), and exports key timing data (position, heading angle, rudder angle) to Excel for subsequent analysis.
openknowledgenp / Election Nepal DataCollection of Election Nepal Project Data in CSV Format
hendisantika / Spring Boot Excel Csv PdfThis is a very simple Project that showcase Export Excel (using AbstractXlsView), Csv (By extending AbstractView) and PDF.
footballcsv / Footballcsv.github.iofootball.csv website, docs, help & support - Add your tools & scripts here! Add your project here!
kerpz / ArduinoEnergyLoggerAn arduino code that reads Current Transformer (CT sensor) data, SRNE Mppt controller data, and SNAT PSW inverter. The data collected will be transmit to a HTTP server via POST with a CSV formatted data. The device used in this project is Wemos D1 mini.
avs-abhishek123 / Twitter Sentimental AnalysisAn AI project where we do web scrapping from Twitter API, find the sentimental analysis using bag-of-word model, & store it in a csv file.
