Hi maheshakya, give me sometime to go through your ML package. Do current product have any stream data support?. i did some university projects related to machine learning with regressions,modelling, factor analysis, cluster analysis and classification problems (Discriminant Analysis) with SVM (Support Vector machines), Neural networks, LS classification and ML(Maximum likelihood). give me sometime to see how wso2 architecture works.then i can come up with good architecture.thank you. BR, Mahesh.
On Wed, Mar 2, 2016 at 2:41 PM, Mahesh Dananjaya <[email protected]> wrote: > Hi Maheshakya, > Thank you for the resources. I will go through this and looking forward to > this proposed project.Thank you. > BR, > Mahesh. > > On Wed, Mar 2, 2016 at 1:52 PM, Maheshakya Wijewardena < > [email protected]> wrote: > >> Hi Mahesh, >> >> Thank you for the interest for this project. >> >> We would like to know what type of similar projects you have worked on. >> You may have seen that WSO2 Machine Learner supports several learning >> algorithms at the moment[1]. This project intends to leverage the existing >> algorithms in WSO2 Machine Learner to support streaming data. As an >> initiative, first you can get an idea about what WSO2 Machine Learner does >> and how it operates. You can download WSO2 Machine Learner from product >> page[2] and the the source code [3]. ML is using Apache Spark MLLib[4] for >> its' algorithms so it's better to read and understand what it does as well. >> >> In order to get an idea about the deliverables and the scope of this >> project, try to understand how Spark streaming[5] (see examples) handles >> streaming data. Also, have a look in the streaming algorithms[6][7] >> supported by MLLib. There are two approaches discussed to employ >> incremental learning in ML in the project proposals page. These streaming >> algorithms can be directly used in the first approach. For the other >> approach, the your implementation should contain a procedure to create mini >> batches from streaming data with relevant sizes (i.e. a moving window) and >> do periodic retraining of the same algorithm. >> >> To start with the project, you will need to come up with a suitable plan >> and an architecture first. >> >> Please watch the video referenced in the proposal (reference: 5). It will >> help you getting a better idea about machine learning algorithms with >> streaming data. >> >> Let us know if you need any help with these. >> >> Best regards >> >> [1] https://docs.wso2.com/display/ML110/Machine+Learner+Algorithms >> [2] http://wso2.com/products/machine-learner/ >> [3] >> https://docs.wso2.com/display/ML110/Building+from+Source#BuildingfromSource-Downloadingthesourcecheckout >> [4] https://spark.apache.org/docs/1.4.1/mllib-guide.html >> [5] https://spark.apache.org/docs/1.4.1/streaming-programming-guide.html >> [6] >> https://spark.apache.org/docs/1.4.1/mllib-linear-methods.html#streaming-linear-regression >> [7] >> https://spark.apache.org/docs/1.4.1/mllib-clustering.html#streaming-k-means >> >> On Wed, Mar 2, 2016 at 1:19 PM, Mahesh Dananjaya < >> [email protected]> wrote: >> >>> Hi all, >>> I am interesting on contribute to proposal 6: "Predictive analytic with >>> online data for WSO2 Machine Learner" for GSOC2 this time. Since i have >>> been engaging with some similar projects i think it will be a great >>> experience for me. Please let me know what you think and what you suggest. >>> I have been going through your documents.thank you. >>> regards, >>> Mahesh Dananjaya. >>> >>> >>> _______________________________________________ >>> Dev mailing list >>> [email protected] >>> http://wso2.org/cgi-bin/mailman/listinfo/dev >>> >>> >> >> >> -- >> Pruthuvi Maheshakya Wijewardena >> [email protected] >> +94711228855 >> >> >> >
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