Because data transformation is where it all begins
Count the number of drivers available in the given area.
Get trading statistics about the last hour of trading
PythonFinancial Market Forecasting
Count the number of rides recently requested in the given area.
Compute the mean and standard deviation of ride durations.
Analyse closing prices seen over different timespans.
SparkSQLFinancial Market Forecasting
Analyse stock trades made each day.
Determine the popularity of a candidate product by analyzing its visit count, cart additions, and purchase frequency.
SparkSQLSearch and Ranking
Aggregate a user’s historical interactions with all product categories.
Identify by how many standard deviations the current transaction amount deviates from the mean transaction amount for a user.
Statistically capture the popularity of a product.
Examine the number of transactions made by a user at the same merchant in the 30 minutes immediately preceding the current transaction time.
Measure the degree to which a user’s recent transactions differ from their usual behavior.
Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!
However, we are currently looking to interview members of the machine learning community to learn more about current trends.
If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.
Interested in trying Tecton? Leave us your information below and we’ll be in touch.