ODSC 2019

Proposal

Time Series Analysis in Python Workshop

Time is precious so is Time Series Analysis”

Time series analysis has been around for centuries helping us to solve from astronomical problems to business problems and advanced scientific research around us now. Time stores precious information, which most machine learning algorithms don’t deal with. But time series analysis, which is a mix of machine learning and statistics helps us to get useful insights. Time series can be applied to various fields like economy forecasting, budgetary analysis, sales forecasting, census analysis and much more. In this workshop, We will look at how to dive deep into time series data and make use of deep learning to make accurate predictions.

Structure of the workshop goes like this

Introduction to Time series analysis
Time Series Exploratory Data Analysis and Data manipulation with pandas
Forecast Time series data with some classical method (AR, MA, ARMA, ARIMA, GARCH, E-GARCH)
Introduction to Deep Learning and Time series forecasting using MLP and LSTM
Forecasting using XGBoost
Financial Time Series data

Libraries Used:

install libraries using pip install -r requirements.txt

Keras (with Tensorflow backend)
jupyter
matplotlib
pandas
statsmodels
sklearn
seaborn
arch
xgboost

Outline/Structure of the Workshop

Introduction to Time series analysis (10 mins)
Time Series Exploratory Data Analysis and Data manipulation with pandas (45 mins)
Forecast Time series data with some classical method (AR, MA, ARMA, ARIMA, GARCH, E-GARCH) (60 mins)
Introduction to Deep Learning and Time series forecasting using MLP and LSTM (60 mins)
Forecasting using XGBoost - (20 mins)
Financial Time Series data - (30 Mins)

Note: Session timings including exercises for attendees to work on

Prerequisites for Attendees