Have you wondered how taxi aggregators like Uber, calculate the price of your trip?
Have you wondered how different factors affect the overall price??
In this workshop, we will look at understanding the factors that affect a taxi fare and build a model which can predict the fare of a trip.
Join us on Saturday, 19th of January as Byte Academy presents you yet another free workshop on Data Science where we will look at understanding the factors that affect a taxi fare and build a model which can predict the fare of a trip.
Topic: Predicting Taxi Fares- A Machine Learning Approach
1. Describing the Problem Statement 2. A brief overview of CRISP-DM Framework to approach any Analytical Problem 3. Overview of the dataset 4. Understanding the various variables and their impact. 5. A brief overview of Regression vs Classification. 6. Importance of Cross-Validation and having a validation dataset describe in brief about Bias vs Variance Tradeoff 7. Understanding the Evaluation Metrics 8. Building & Evaluating the models 9. Importance of Feature Engineering and its impact 10. Q&A
About the Speaker: Aishwarya Ramachandran is a News Analyst in Thomson Reuters with 1.5 years of experience in deploying primary and secondary research techniques to derive Reporting Analysis, understanding customer segments and performing competition analysis thus facilitating achievement of companies growth objectives. She is also an active writer on medium.com with articles published in Analytics Vidhya Medium publication.
Byte Academy (Byte) is a leader in industry oriented technology education with courses in Python software development, FinTech, Data Science and Blockchain. Byte provides short format immersive boot camps in industry-relevant technologies and is recognized for small classes, career assistance and sense of community. We established the first FinTech program in the world and also the first Python full-stack software development boot-camp in New York City, where it is headquartered.