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A python package for interaction with time series data.
My invited Keynote/Talk at Conferences, Universities, Companies, etc.
This notebook was built to analyze Whatsapp conversations using the steps below: Step 1: Detecting {Date} and {Time} tokens Step 2: Detecting the {Author} token Step 3: Extracting and Combining tokens Step 4: Parsing the entire file and handling Multi-Line Messages For further steps, we need to perform Exploratory data analysis (EDA) Step 5: Performing EDA for analyzing chat data Step 6: Overall statistics of WhatsApp chat including Total number of messages, media messages(Omitted) & Total number of URLs Step 7: Extracting basic statistics for each Author (user) Step 8: Word cloud of most used words in chat Step 9: Total number of messages sent by each user Step 10: Total messages sent on each day of the week Step 11: Most active author of the chat Step 12: Most active day in a week In next steps, Time series analysis will be performed on chat data Step 13: Time whenever the chat was highly active Step 14: Date on which the chat was highly active Step 15: Converting 12-hour formate to 24 hours will help us for better analysis Step 16: Most suitable hour of the day whenever there will be more chances of getting a response from user
NW.UnivariateForecasting is a library to perform Univariate Forecasting on your own values. Time Series Forecasting is a machine learning technique that aims to predict the next values in a time series when a subset of subsequent values is provided ("sliding window").
📈💼✈️ Welcome to ForecastAIHub! Our repository is dedicated to financial market prediction and flight passenger forecasting. By harnessing powerful AI algorithms, we provide accurate forecasts for market trends and flight demand. 📊💹✈️ Our mission is to empower data-driven decision-making in the realms of finance and aviation.
It's a time series forecast problem that basically solves short term electricity bill of a house hold
This repository contains the assignment of Macro-Econometric Forecasting by IMFx.
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Time Series analysis for the prediction of Daily corona new cases using ARIMA and HoltWinter Model in R programming..
using Fully Connected Network to forecast gold price in January 2024.
Rによる経済予測シミュレーション
Capstone Project - IIT Palakkad Applied Data Science Program
Pedictive Analysis | Time Series | Forecasting | R Programming