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[Docs] Fixed typo: ROADMAP.md #55

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Merged
merged 2 commits into from
May 7, 2018
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[Docs] Fixed typo: ROADMAP.md #55

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27974d3
Remove unnecessary char
yamachu May 7, 2018
4030bb5
Fixed typo
yamachu May 7, 2018
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4 changes: 2 additions & 2 deletions ROADMAP.md
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Expand Up @@ -46,7 +46,7 @@ In the meanwhile, we are looking for contributions. An easy place to start is t
* Generative Additive Models
* [SymSGD](https://arxiv.org/pdf/1705.08030.pdf) -a fast linear SGD learner
* Factorization Machines
* [ProtoNN and Bonsaii](https://www.microsoft.com/en-us/research/project/resource-efficient-ml-for-the-edge-and-endpoint-iot-devices/) for compact and effecient models
* [ProtoNN and Bonsaii](https://www.microsoft.com/en-us/research/project/resource-efficient-ml-for-the-edge-and-endpoint-iot-devices/) for compact and efficient models
* Integration with other ML packages
* Accord.NET
* etc.
Expand All @@ -56,7 +56,7 @@ In the meanwhile, we are looking for contributions. An easy place to start is t
* Hybrid training of pipelines containing both DNN and non-DNN predictors
* Additional ML tasks (*)
* _Recommendation_ - Is a problem that can be phrased a: "For a given user, predict the ratings this user would give to the items that they have not explicitly rated yet"
* _Anomaly Detection_, also known as _outlier detection_. It is a task to identify items, events or observations which do not conform to an expected pattern in the dataset. Typical examples are: detecting credit card fraud, medical problems or errors in text. Anomalies are also referred to as outliers, �novelties, noise, deviations and exceptions
* _Anomaly Detection_, also known as _outlier detection_. It is a task to identify items, events or observations which do not conform to an expected pattern in the dataset. Typical examples are: detecting credit card fraud, medical problems or errors in text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions
* _Sequence Classification_ - learns from a series of examples in a sequence, and each item is assigned a distinct label, akin to a multiclass classification task
* Additional Data source support
* Data from SQL Databases, such as SQL Server
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