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web-traffic-time-series-forecasting-6

Forecast future traffic to Wikipedia pages

web-traffic-time-series-forecasting-7

web-traffic-time-series-forecasting-8

web-traffic-time-series-forecasting-9

web3

Selection of Web3 tools & resources (will be updated regularly) 🥷🏼

web3-flashbots

Web3.py plugin for using Flashbots' bundle APIs

web3py-searcher-minter

Mint an NFT with Flashbots and Python

web_econ

Files for COMPGW02 Web Economics group assignment Group 1

web_econ_individual

web_economics

web_file_downloader

Download all PDF files in single webpage

web_traffic_analysis

Web Traffic Time Series Forecasting, forecast future traffic to Wikipedia pages

web_traffic_forecast

For https://www.kaggle.com/c/web-traffic-time-series-forecasting team

web_traffic_time_series_forecasting

# 65 / 1095 with rolling medians

web_traffic_time_series_forecasting-1

Based on the Kaggle competition "Web Traffic Time Series Forecasting (https://www.kaggle.com/c/web-traffic-time-series-forecasting) It uses an ARIMA model to predict pages visualisation. It use the key_2.csv file from the Kaggle competition page with the list of pages and dates for each page to predict, and use the train_2.csv file as training dataset

web_traffic_time_series_forecasting-2

web_traffic_time_series_forecasting-3

92nd Place Solution in the competition organized by Kaggle

webcam-pulse-detector

A python application that detects and highlights the heart-rate of an individual (using only their own webcam) in real-time.

webppl_to_lambda_serverless

Deploying a webppl probabilistic program as an (AWS lambda) endpoint.

webscraping1

Web scraping mini project -1 (countries)

webscraping_twittersentimentanalysis

To Scrape IMDB for Celebrity Data and Analyze Sentiment on Twitter | Edureka Course Work

webservicestudio

WebServiceStudio

website

Personal website

website-classification-ptm-naive

This project started as a attempt to successfully implement a famous sequential pattern mining algorithm. But eventually it turned to a classifier that uses the frequent pattern discovery method given to identify patterns and classify documents.

website-traffic-prediction

Forecasting website traffic using facebook's Prophet Library (Time series)

webtraffic

EDA and simple modelling for the WebTraffic of Wikipedia. Kaggle: https://www.kaggle.com/c/web-traffic-time-series-forecasting

webtrafficforecasting

Web traffic over pages have been foretasted using "TIME SERIES- ARIMA, BOOSTING METHODS OF REGRESSION and PROPHET".

week-7-ip

Overview As a Data Scientist, you work for Hass Consulting Company which is a real estate leader with over 25 years of experience. You have been tasked to study the factors that affect housing prices using the given information on real estate properties that was collected over the past few months. Later onwards, create a model that would allow the company to accurately predict the sale of prices upon being provided with the predictor variables. Within your deliverable you are expected to: Define the question, the metric for success, the context, experimental design taken. Read and explore the given dataset. Define the appropriateness of the available data to answer the given question. Find and deal with outliers, anomalies, and missing data within the dataset. Perform univariate, bivariate and multivariate analysis recording your observations. Performing regression analysis. Incorporate categorical independent variables into your models. Check for multicollinearity Provide a recommendation based on your analysis. Create residual plots for your models, and assess heteroskedasticity using Barlett's test. Challenge your solution by providing insights on how you can make improvements in model improvement. While performing your regression analysis, you will be required to perform modeling using the given regression techniques then evaluate their performance. You will be then required to provide your observations and recommendation on the suitability of each of the tested models on their appropriateness of solving the given problem. Multiple Linear Regression Quantile Regression Ridge Regression Lasso Regression Elastic Net Regression

weibull-adstock

Modeling adstock in media mix modeling using Weibull transformations.

weight-loss

Machine Learning meets ketosis: how to effectively lose weight