maverick
Aspice, officio fungeris sine spe honoris ampliori
Read Fastlane!
Read Unscripted!
Speedway Pass
User Power
Value/Post Ratio
228%
- Oct 26, 2012
- 605
- 1,380
I manage a team of data scientists and engineers at a big corporate. I'm going to be blunt here so brace yourself.
Your target audience needs to be more specific. Who do you mean by 'data scientists'? Who is your ideal customer? On your website, you also seem to use data scientists and engineers interchangeably.
I'm sure you know that ingesting, parsing and pre-processing data is very time consuming, especially at corporates. Same for exposing outputs to end users. How does this work with your product?
I'll give you an example.
I create a demand forecast model for an ice cream brand. Objective is to predict what sales will be over the coming 30 days. We will use historical sales data and merge it with weather data from an external party. In short, the phases we need to go through are:
Ingesting => Parsing => Pre-processing => Modelling => Evaluating
Where does your product fit in? How would I use your product? What is the added benefit of using your product instead of alternatives (e.g. open source libraries)? How does this differ from jupyter notebooks?
Your target audience needs to be more specific. Who do you mean by 'data scientists'? Who is your ideal customer? On your website, you also seem to use data scientists and engineers interchangeably.
- Data scientists working on start-ups?
- Data scientists working at corporates?
- BI / Developers looking to integrate machine learning in their existing products?
- BI/ Developers looking to integrate machine learning in new products?
- Data engineers?
I'm sure you know that ingesting, parsing and pre-processing data is very time consuming, especially at corporates. Same for exposing outputs to end users. How does this work with your product?
I'll give you an example.
I create a demand forecast model for an ice cream brand. Objective is to predict what sales will be over the coming 30 days. We will use historical sales data and merge it with weather data from an external party. In short, the phases we need to go through are:
Ingesting => Parsing => Pre-processing => Modelling => Evaluating
Where does your product fit in? How would I use your product? What is the added benefit of using your product instead of alternatives (e.g. open source libraries)? How does this differ from jupyter notebooks?