Fun in the Playground

Why write a blog about how to build a neural net classifier when you can visualize how it works in the awesome Tensorflow Playground? See the link to start playing.

https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.70210&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false

Value from Verbatim

Want to reduce complaints, focus on customer priorities and reduce churn? You can do this by using Natural Language Processing (NLP) and customer profiling. We convert text to metrics, and then to emotions. This helps quantify what is important, and then allows tracking of impact to ensure the best reactions to customer feedback.

There is no point listening if there is no action! Algospark build tailored frameworks for feedback that track, aggregate and map insights. Verbatim feedback quantification is a key foundation to building strong customer relations. See a basic example here

https://wilkinsondi.shinyapps.io/verbatim_insights/

Get in touch to discuss how this can help you improve your monitoring and response to the voice of the customer.

Premier League AI

Football is predictable?

We are predicting that Arsenal win the Arsenal v Chelsea fixture this weekend. We use an ensemble of three AI models to predict home, draw or win results. Our models use player data, manager data and 5 year historic fixtures data to determine most likely outcomes.

https://algospark.shinyapps.io/premierleague/

We calculate match outcome probabilities, decimal odds implied from these probabilities and how the predictions performed last week. The matches are ranked in order of confidence of the prediction (from high to low).

Don’t hesitate to get in touch to discuss further. info@algospark.com

DISCLAIMER: These predictions are guidelines only, Algospark takes no responsbility for the accuracy of information or any losses incurred resulting from decisions are actions taken using these predictions.