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Amazon Machine Learning – Make Data-Driven Decisions at Scale
- minimaxir 11y agoSo the pricing is $100 per million data points, at minimum. That doesn't seem like it scales well for big data at all. However, that's 5x cheaper than what BigML is offering (https://bigml.com/pricing/credits https://bigml.com/pricing/credits) for its ad hoc service, so I might be wrong.
- aficionado 11y agoBigML cofounder here. Most BigML customers doing machine learning at scale use either BigML subscriptions (starting $30/mo) or private deployments – both of which provide unlimited model training and predictions and are suitable for developers and large enterprises alike. In addition, with BigML you can export your models (for cluster analysis and anomaly detection and not just classification/regression) to run locally and/or to be incorporated in related systems and services.
- addisonj 11y agoAt first glance, this looks to go somewhat beyond Google's Prediction API, which (at least from my experience) is pretty limited in its usefulness. Its nice to see tools for analyzing your data as well as multi-class classification, and some tune-able parameters but this doesn't seem to bring anything 'new' to the game. All the hard parts, feature selection, noise, unlabeled data, etc are still up to the end user, which makes me wonder how many people will try this out and get poor results. It would be nice to get an idea of what sort of model they are using on the backend or even having a choice of models.
- gallamine 11y agoThe system also uses logistic regression and is limited to 100 gb dataset. Prediction with LR isn't that expensive and training can be done online with something like stochastic gradient descent. That can be done on a single computer. Given that the models aren't exportable and you can import a model, I'm hard pressed to see the immediate value. Long term, though, I'm sure there's plenty of growth.
- deleted 11y ago[deleted]
- alooPotato 11y agoWhat differences did you notice beyond Google's Prediction API?
- addisonj 11y agoThis may be different now, but when I used Prediction API a few years ago, I don't remember it having any data analysis tools or multi-class classification. The UI was also pretty lacking. Haven't looked at in a while but perhaps it has gotten better?
- huac 11y agoIt's kind of unclear, but it looks from the screenshots as if AWS is doing feature selection behind the scenes. But it seems that unless AWS does feature selection or model selection really efficiently behind the scenes, the cost of that extra work time is placed on the user.
- pinkunicorn 11y agoI am really amazed at the kind of things Amazon turns into a service. And this ML service is just wow'ing. I have fiddled with basic SVM's before, but this takes away the part of writing code and makes it sort of a end user product(you are still expected to know basics about ML). On the other hand, I also don't think this will take off very well. Maybe a few companies/startups who have cash in their pocket will use it/try it out, but the audience is really limited beyond that in my opinion.
- gallamine 11y ago> Maybe a few companies/startups who have cash in their pocket will use it/try it out Honestly, I'd see it the other way around. Small companies without a DS team might be drawn to this. I don't see how any company with a lick of sense would lock down their prediction model into AWS. They very clearly won't let you export your model once the training is done.
- minimaxir 11y agoSmall companies without a DS team will likely fall into the ML pitfalls which make the resulting analysis invalid.
- cfeduke 11y ago> Maybe a few companies/startups who have cash in their pocket will use it/try it out This would be really nice to use at my startup, but its cost prohibitive even on a very large budget. I am setting up Spark Streaming to handle model creation and updates for recommendations based on what a user interacts with. If I were to even attempt something similar with this AWS service, its $10 for every 1 million predictions which isn't sustainable (not including the costs to create and update the model). > but the audience is really limited beyond that in my opinion. Definitely, largely as a result of cost. I would love to not have to worry about Spark in my infrastructure (its another piece...) but at this price the AWS service is just too expensive.
- Xorlev 11y ago
- discardorama 11y agoDid they basically just put a wrapper around VW[1] ? [1] https://github.com/JohnLangford/vowpal_wabbit https://github.com/JohnLangford/vowpal_wabbit
- Xorlev 11y agoOr Weka.
- BenoitP 11y ago> at scale I'd say Apache Spark
- mturmon 11y agoNo -- see https://aws.amazon.com/machine-learning/faqs/ https://aws.amazon.com/machine-learning/faqs/ -- "Q: What algorithm does Amazon Machine Learning use to generate models? Amazon Machine Learning currently uses an industry-standard logistic regression algorithm to generate models." But disappointingly: "Q: Can I export my models out of Amazon Machine Learning? No. Q: Can I import existing models into Amazon Machine Learning? No." Note that they are doing classification and regression on iid feature vectors. Of course, ML is much larger than this setting, but this setting is generic enough that it has some applicability to lots of problems.
- etrain 11y agoThis does not mean they are not using Vowpal Wabbit. It is very easy to run Vowpal Wabbit with a logistic loss function. Also, vw is what I'd consider "industry standard."
- deleted 11y ago[deleted]
- ris 11y agoYeah sure, why not make your business process depend on a closed proprietary cloud-based product? (in all fairness Amazon are better than many when it comes to unexpectedly withdrawing products)
- psaintla 11y agoI would be less worried about that and more worried about cost. I know of two different startups that aren't profitable but would be if they hadn't put their entire platform on amazon services. One of those startups was lucky enough to be acquired but it's going to take them many unprofitable years to migrate away.
- vmarsy 11y agoIs it just Amazon's catching up with Azure ML launched last year? (And cutting prices by 80%) Azure ML also supports R and Python custom code, which can be dropped directly into your workspace. And this was even before Microsoft acquired Revolution Analytics. Amazon ML seems to be less flexible in regards to importing your own models: Q: Can I export my models out of Amazon Machine Learning? No. Q: Can I import existing models into Amazon Machine Learning? No. http://blogs.microsoft.com/blog/2014/06/16/microsoft-azure-machine-learning-combines-power-of-comprehensive-machine-learning-with-benefits-of-cloud/ http://blogs.microsoft.com/blog/2014/06/16/microsoft-azure-m... https://aws.amazon.com/machine-learning/faqs/ https://aws.amazon.com/machine-learning/faqs/ http://azure.microsoft.com/en-us/services/machine-learning/ http://azure.microsoft.com/en-us/services/machine-learning/
- aficionado 11y agoNo... it's Amazon ML and Azure ML trying to catch up with BigML. They copied many things from our service but forgot to copy the ease of use. Services like Azure ML, Amazon ML and even Google Predict API work like a black box, and lock your model away, making you extremely dependent on their proprietary service. With BigML, you can easily export your models and use them anywhere for free. If the goal is to democratize machine learning, then the ability to extract your models and use them as you see fit is essential, and only BigML offers that level of freedom.
- okisan 11y agoI just try out BigML and look awesome. I use Google Prediciton API to fill a value on form of a web request. I need the result immediately. Why BigML require two web request and take so long to get a prediction of a trained model?
- aficionado 11y agoIf you use BigML's web forms, the first request caches the model locally so that all the subsequent predictions are performed directly in your browser.
- sandstrom 11y agoCannot find it (in N. Virginia)? Is that only me? (if anyone has the direct link for the console, please share :)
- rm999 11y agoMeh. The more I do machine learning in industry the more I realize how little the ML part matters compares to everything else. A typical project I've seen takes 3-6 months and contains thousands lines of code, but the machine learning part will take a week or two and be 100 lines of code. What Amazon ML is doing would probably take an hour and 30 lines of R code you can easily find online. And here's the not-too-hidden secret: the ML part is the fun part. It's a big reason we spend months creating banking.csv. Josh Willis did a very funny presentation at MLconf partly about this. It's like waiting in line at a theme park for an hour, and then paying someone to cut in line at the last minute and record the ride for you. https://www.youtube.com/watch?v=4Gwf5zsg4vI&feature=youtu.be&t=657 https://www.youtube.com/watch?v=4Gwf5zsg4vI&feature=youtu.be...
- sgt101 11y agoThis. The pity is that immediately we get the results after a week the project is over and we move back to data wrangling hell!
- deleted 11y ago[deleted]
- benhamner 11y agoYou hit the nail on the head. Completely agrees with all my experience at Kaggle and applying machine learning across a broad number of industries
- Gimpei 11y agoIsn't the point here that you can do it on huge datasets that don't work nicely with R
- noelsusman 11y agoThere are plenty of tools for that already. The point here is to make it as easy as possible. I guess this could be useful for some people, but it seems rudimentary to me. If I'm reading their FAQ right they're just fitting a logistic regression to everything. I'm hoping this is just a starting point. Also, not being able to export the actual model seems like a huge dealbreaker to me.
- rcpt 11y agoSome have already taken this kinda thing a few steps further: http://www.automaticstatistician.com/ http://www.automaticstatistician.com/
- orionblastar 11y agoI predict we will see more cloud based machine learning services. Since machine learning is hard to learn and write for the average person, providing the services will greatly help them. It would be good if there were an open source tool like Libreoffice that does Machine Learning in their spreadsheet app. It would be a good feature to add, and then the competitors would have to add it to their software as well.
- saurabhtandon 11y agoI like the "Introduction to Machine Learning" which sort of briefly outlines the basics of machine learning for people who don't know about it.
- aficionado 11y agoDid anyone actually give it a try? I only get this error with any dataset (even a humble Iris): Amazon ML cannot create an ML model: 1 validation error detected: Value null at 'predictiveModelType' failed to satisfy constraint: Member must not be null
- mloudon 11y agogo to the datasources tab and see if there's an error message from data source creation. i had the same error due to an issue with variable names.
- chrischen 11y agoGoogle's competing product: https://cloud.google.com/prediction/docs https://cloud.google.com/prediction/docs