Time Series based Data Analytics for Taxi Services

About the Webinar

Time series data is an ordered sequence of observations of well-defined data items at regular time intervals. Examples include daily exchange rates, bank interest rates, monthly sales, heights of ocean tides, or humidity. Time Series Analytics is useful in predicting future values or detecting anomalies across a variety of application areas.

Agenda

1. What is Time Series Analytics
2. Why to use Time Series Analytics
3. Understanding Taxi Service Database
4. Predicting availability or price prediction using Time Series Analysis

About the Speaker

My Ankit is Data scientist with four years of experience in providing data driven solutions to complex business problems in predictive and inquisitive analytics domain to Fortune 500 Companies. In-depth knowledge with experience of using multiple machine learning algorithms (for classification, Regression, and clustering) and statistical techniques for hypothesis testing in the inference/prediction models created for the projects.