Data Smart: Using Data Science to Transform Information into Insight

“Why didn't you use support vector machines or neural nets or random forests or boosted trees?” There are numerous types of AI models all with their strengths and weaknesses. And I would encourage you to read about them, and if in your

You can use it to classify company e-mails, customer support transcripts, AP wire articles, the police blotter, medical documents, movie reviews, whatever!

just cleverly turns past data into a formula or set of rules that it uses to predict a future case. As we saw in the case of naïve Bayes in Chapter 3, it's the AI model's ability to recall this data and associated decision rules, probabilities, or coefficients that make it so effective.

It's spent moving data to send through the AI model. It's not spent running the AI model, and it's certainly not spent training the AI model.

media. One example is the congressional discussion around NSA's ability to perform a “three-hop” query—that is go into their network graph of phone call data and find people three hops from a known terrorist (nodes connected to a terrorist by a three edge path in the graph). Whatever your business is, I guarantee you have a graph hiding in your dat

AI is useful across nearly any industry you can think of. Your credit card company uses it to identify odd transactions on your account. The enemy in your shoot-em-up Xbox game runs on AI. There's e-mail spam filtering, tax fraud detection, spelling auto-correction, and friend recommendation on social networks.

Artificial intelligence is making waves these days for its use at tech companies and start-ups. Optimization, on the other hand, seems to be more of a Fortune 500 business practice.

Identify the analytics opportunities you want to tackle in as much detail as possible before acquiring tools.

best model is one that strikes the right balance between functionality and maintainability. If an analytics model is never used, it's worthless.