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Machine Learning in Real-time
Predicting Taxi Fare in NYC
Today, the benefit of Machine Learning is conditioned to its deployment in real-time. In this talk, Adam Jelley, Data Scientist, will explain how to deploy a real-time taxi fare prediction engine to power an Uber-like application. Along the cycle of developing such a project, he will highlight key lessons learned, like understand the problem before building models, do not add features for the sake of features, try as many algorithms as possible, and simplify your pipeline before deployment.
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| Rating | Not enough ratings |
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| Length | 0.4 hours |
| Starts | On Demand (Start anytime) |
| Cost | $35/month (Access to entire library- free trial available) |
| From | Pluralsight |
| Instructor | Big Data LDN |
| Download Videos | On Windows, MacOS, iOS, and Android Pluralsight app |
| Language | English |
| Subjects | IT & Networking |
| Tags | Data Professional |
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| Rating | Not enough ratings |
|---|---|
| Length | 0.4 hours |
| Starts | On Demand (Start anytime) |
| Cost | $35/month (Access to entire library- free trial available) |
| From | Pluralsight |
| Instructor | Big Data LDN |
| Download Videos | On Windows, MacOS, iOS, and Android Pluralsight app |
| Language | English |
| Subjects | IT & Networking |
| Tags | Data Professional |
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