Competitions overview

Winning a Kaggle Competition in Python

Yauhen Babakhin

Kaggle Grandmaster

Instructor

Yauhen Babakhin

Master’s Degree in Applied Data Analysis
5 years of working experience in Data Science
Kaggle competitions Grandmaster
Gold medals in both classic Machine Learning and Deep Learning competitions

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Kaggle benefits

Get practical experience on the real-world data
Develop portfolio projects
Meet a great Data Science community
Try new domain or model type
Keep up-to-date with the best performing methods

Competition process

kaggle competition process

Competition process

kaggle competition process

Competition process

kaggle competition process

How to participate

Go to http://kaggle.com website and select the competition
Download the data
Start building the models!

New York city taxi fare prediction

New York city taxi fare prediction page

Train and Test data

import pandas as pd

# Read train data
taxi_train = pd.read_csv('taxi_train.csv')
taxi_train.columns.to_list()

['key',
 'fare_amount',
 'pickup_datetime',
 'pickup_longitude',
 'pickup_latitude',
 'dropoff_longitude',
 'dropoff_latitude',
 'passenger_count']

# Read test data
taxi_test = pd.read_csv('taxi_test.csv')
taxi_test.columns.to_list()

['key',
 'pickup_datetime',
 'pickup_longitude',
 'pickup_latitude',
 'dropoff_longitude',
 'dropoff_latitude',
 'passenger_count']

Sample submission

# Read sample submission
taxi_sample_sub = pd.read_csv('taxi_sample_submission.csv')
taxi_sample_sub.head()

                              key     fare_amount
0     2015-01-27 13:08:24.0000002     11.35
1     2015-01-27 13:08:24.0000003     11.35
2     2011-10-08 11:53:44.0000002     11.35
3     2012-12-01 21:12:12.0000002     11.35
4     2012-12-01 21:12:12.0000003     11.35

Let's practice!

Winning a Kaggle Competition in Python