https://github.com/jacktheprogrammer/time-series-forecasting-and-analysis
My personal project consisting of my personally created notebooks to work with time series forecasting and analysis. In these projects, I've used deep learning using tensorflow, xgboost, statsmodels and scipy libraries of python. The series were of weather, energy consumption and that of stocks.
https://github.com/jacktheprogrammer/time-series-forecasting-and-analysis
data-analysis data-science deep-neural-networks energy-consumption machine-learning portfolio prophet-facebook prophet-model python python3 scipy statsmodels stocks tensorflow time-series time-series-analysis timeseries-forecasting weather xgboost
Last synced: about 1 month ago
JSON representation
My personal project consisting of my personally created notebooks to work with time series forecasting and analysis. In these projects, I've used deep learning using tensorflow, xgboost, statsmodels and scipy libraries of python. The series were of weather, energy consumption and that of stocks.
- Host: GitHub
- URL: https://github.com/jacktheprogrammer/time-series-forecasting-and-analysis
- Owner: JackTheProgrammer
- Created: 2025-02-12T18:48:48.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-12T21:10:48.000Z (3 months ago)
- Last Synced: 2025-02-12T22:22:43.689Z (3 months ago)
- Topics: data-analysis, data-science, deep-neural-networks, energy-consumption, machine-learning, portfolio, prophet-facebook, prophet-model, python, python3, scipy, statsmodels, stocks, tensorflow, time-series, time-series-analysis, timeseries-forecasting, weather, xgboost
- Language: Jupyter Notebook
- Homepage:
- Size: 21.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Time Series Analysis & Forecast
My personal project consisting of my personally created notebooks to work with time series forecasting and analysis.
## Techniques & Methodology applied
In these projects, I've used deep learning using tensorflow, xgboost, statsmodels and scipy libraries of python.
## Series worked with
The series were of weather, energy consumption and that of stocks.
# Learning resources
* [Complete course of time series analysis and forecasting in Hindi](https://youtu.be/A3fowDMo8mM?si=4V9STjaMadRrQJF2 "Video")
* [Time series using Prophet](https://youtu.be/z3ZnOW-S550?si=G_rhS1qhL3Kn9xGh "Video")
* [Prophet facebook docs](https://facebook.github.io/prophet/docs/quick_start.html#python-api "Docs")
* [Time series using XGBoost](https://youtu.be/vV12dGe_Fho?si=9b6eT7lpP7Q-vT5P "Video")
* [Single variate time series forecasting using deep neural network](https://youtu.be/c0k-YLQGKjY?si=b2WpjKMOGdZWCm0v "Video")
* [Multi variate time series forecasting using deep neural network](https://youtu.be/kGdbPnMCdOg?si=FF4jyt6eosW_KnQB "Video")