I want to create a machine learning programme which takes greyhound racing data and predicts the probability of each greyhound winning for future races.
I think that the Amazon Machine Learning tool could do this but I am open to other suggestions.
To start with I will need to do some data mining to capture the following past data about past races.
1. Trap
2. Race Distance
3. Track
4. Days since last race
5. Split
6. Sex of dog
7. Finishing time
8. Grade of race
Suggested sources for this data are:
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http://greyhoundbet.racingpost.com/#dog/race_id=1453332&r_date=2016-05-27&dog_id=476762
The output should be represented as a percentage chance of each dog winning, which should always add up to 100%. E.g.
Trap 1 10%
Trap 2 20%
Trap 3 35%
Trap 4 5%
Trap 5 15%
Trap 6 15%
I would suggest looking at this link to better understand what I am trying to create.
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Hello
First of all this bid is dummy because I am yet to understand what are we trying to achieve. Is it a research problem or a school assignment or we are really making a system that would help us bid. I can help you in all cases though.
Second it can be done, if there is some pattern in the data we can build a model that recognizes and we have enough data to recognize that pattern; it can surely be achieved.
Third Amazon machine learning is just a collection of tools, similar tools are freely available as well which I use all the time like google Tensorflow. The only time we will need help of amazon if we have GB's of complicated data and our naive machines at home can't process that.
Again I find it interesting what you are trying to do and would like talk to you about that. Feel free to send me a message anytime if you are up for it.
Thanks Man
I have extensive experience with both web scraping and machine learning. If hired, I will return not only your predictions, but also an explanation of how everything works (so you know where the numbers are coming from).