Methods, systems, and apparatus, including computer programs encoded on computer storage media, for centralized management of predictive models. One of the methods includes receiving a plurality of model versions from respective teams within the organization. Each received model version is processed to generate a respective predictive model corresponding to the model version, including identifying one or more collections of training data specified by the model version, identifying one or more training engines specified by the model version, training, by the identified one or more training engines, a predictive model using the identified one or more collections of training data, computing one or more performance metrics for the predictive model, and associating the one or more performance metrics for the predictive model with the corresponding model version in the version repository.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for centralized management of predictive models within an organization, the system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a plurality of model versions from respective teams within the organization, wherein each model version is a collection of data that specifies one or more maintained collections of training data and one or more training engines for generating a predictive model from the one or more maintained collections of training data; storing each of the plurality of model versions in a version repository; and processing each received model version to generate a respective predictive model corresponding to the model version, including: identifying one or more collections of training data specified by the model version, identifying one or more training engines specified by the model version, training, by the identified one or more training engines, a predictive model using the identified one or more collections of training data, computing one or more performance metrics for the predictive model, and associating the one or more performance metrics for the predictive model with the corresponding model version in the version repository. 2. The system of claim 1, wherein at least one of the received model versions is a forked model version that reuses one or more features from another model in the version repository. 3. The system of claim 1, wherein at least one of the received model versions is a merged model version that combines features of one or more other models in the version repository. 4. The system of claim 1, wherein the operations further comprise: obtaining performance metrics associated with each of the model versions in the version repository; determining that one of the model versions has a performance metric indicating underperformance relative to the other model versions; and generating a notification to a team responsible for the underperforming model version. 5. The system of claim 4, wherein the operations further comprise grouping each of the model versions into a same category. 6. The system of claim 1, wherein the operations further comprise: receiving an indication of a proposed new model version; determining that one or more similar model versions already exist in the version repository; and generating a notification to a team responsible for the proposed new model version, wherein the notification indicates the availability of the one or more similar model versions that already exist in the version repository. 7. The system of claim 1, wherein the operations further comprise: receiving an indication that a particular collection of training data is obsolete; obtaining, from the version repository, identifiers of all model versions that utilize the obsolete collection of training data; and generating a notification to each respective team responsible for a model version that utilizes the obsolete collection of training data. 8. A computer-implemented method comprising: receiving a plurality of model versions from respective teams within the organization, wherein each model version is a collection of data that specifies one or more maintained collections of training data and one or more training engines for generating a predictive model from the one or more maintained collections of training data; storing each of the plurality of model versions in a version repository; and processing each received model version to generate a respective predictive model corresponding to the model version, including: identifying one or more collections of training data specified by the model version, identifying one or more training engines specified by the model version, training, by the identified one or more training engines, a predictive model using the identified one or more collections of training data, computing one or more performance metrics for the predictive model, and associating the one or more performance metrics for the predictive model with the corresponding model version in the version repository. 9. The method of claim 8, wherein at least one of the received model versions is a forked model version that reuses one or more features from another model in the version repository. 10. The method of claim 8, wherein at least one of the received model versions is a merged model version that combines features of one or more other models in the version repository. 11. The method of claim 8, further comprising: obtaining performance metrics associated with each of the model versions in the version repository; determining that one of the model versions has a performance metric indicating underperformance relative to the other model versions; and generating a notification to a team responsible for the underperforming model version. 12. The method of claim 11, further comprising grouping each of the model versions into a same category. 13. The method of claim 8, further comprising: receiving an indication of a proposed new model version; determining that one or more similar model versions already exist in the version repository; and generating a notification to a team responsible for the proposed new model version, wherein the notification indicates the availability of the one or more similar model versions that already exist in the version repository. 14. The method of claim 8, further comprising: receiving an indication that a particular collection of training data is obsolete; obtaining, from the version repository, identifiers of all model versions that utilize the obsolete collection of training data; and generating a notification to each respective team responsible for a model version that utilizes the obsolete collection of training data. 15. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a plurality of model versions from respective teams within the organization, wherein each model version is a collection of data that specifies one or more maintained collections of training data and one or more training engines for generating a predictive model from the one or more maintained collections of training data; storing each of the plurality of model versions in a version repository; and processing each received model version to generate a respective predictive model corresponding to the model version, including: identifying one or more collections of training data specified by the model version, identifying one or more training engines specified by the model version, training, by the identified one or more training engines, a predictive model using the identified one or more collections of training data, computing one or more performance metrics for the predictive model, and associating the one or more performance metrics for the predictive model with the corresponding model version in the version repository. 16. The computer program product of claim 15, wherein at least one of the received model versions is a forked model version that reuses one or more features from another model in the version repository. 17. The computer program product of claim 15, wherein at least one of the received model versions is a merged model version that combines features of one or more other models in the version repository. 18. The computer program product of claim 15, wherein the operations further comprise: obtaining performance metrics associated with each of the model versions in the version repository; determining that one of the model versions has a performance metric indicating underperformance relative to the other model versions; and generating a notification to a team responsible for the underperforming model version. 19. The computer program product of claim 18, wherein the operations further comprise grouping each of the model versions into a same category. 20. The computer program product of claim 15, wherein the operations further comprise: receiving an indication of a proposed new model version; determining that one or more similar model versions already exist in the version repository; and generating a notification to a team responsible for the proposed new model version, wherein the notification indicates the availability of the one or more similar model versions that already exist in the version repository. 21. The computer program product of claim 15, wherein the operations further comprise: receiving an indication that a particular collection of training data is obsolete; obtaining, from the version repository, identifiers of all model versions that utilize the obsolete collection of training data; and generating a notification to each respective team responsible for a model version that utilizes the obsolete collection of training data.