Using Data to Predict Bike Share Demand In London Without Code

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Using machine learning to predict demand using no-code machine learning, we created the ideal day when the number of bike-share rentals was the highest in London. We used a dataset that collected data over a year-long period to identify what season the bike share rentals are the highest. Users are more likely to use other forms of transportation (Uber, train, bus) to avoid bad weather. The ideal day for bike share rental is 9.5°C on a non-holiday weekday with a wind speed of 20 km/h.