Main Reference PaperAmazon EC2 Spot Price Prediction using Regression Random Forests, IEEE Transactions on Cloud Computing, 2018 [Python]
  • This work aims to predict the predict the future spot prices. This prediction is done by machine learning based ensemble method namely Regression Random Forests (RRFs). It also feature importances are identified and used by spot users to plan job executions in advance and bid effectively leading to significant cost savings and reducing out-of-bid failure probability of spot instances.

Description
  • This work aims to predict the predict the future spot prices. This prediction is done by machine learning based ensemble method namely Regression Random Forests (RRFs). It also feature importances are identified and used by spot users to plan job executions in advance and bid effectively leading to significant cost savings and reducing out-of-bid failure probability of spot instances.

  • To increase the spot prices prediction accuracy and speed.

  • To minimize the execution costs.

Aim & Objectives
  • To increase the spot prices prediction accuracy and speed.

  • To minimize the execution costs.

  • A technique is contributed to further improve the prediction accuracy.

Contribution
  • A technique is contributed to further improve the prediction accuracy.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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