Machine learning With MongoDB

What is MongoDB?

MongoDB is a NoSQL database that stores JSON-like documents dynamic schema. It is used for storing high-volume data. It makes use of collection and documents. Whereas collection contains sets of documents. It maps to the object in an application that is easier to use and work with. It is used to deploy API.

What is machine learning?

Machine learning is an application of Artificial intelligence that can learn and improve from the experience without even changing the code. Machine learning works on the development of the programs which can access the data and learn from them and improve the data and its accuracy. Machine learning trains the model/algorithms and improves dataset over the time and makes predictions according to the new data.

MongoDB with Machine learning

MongoDB Offers two driver native and certified connectors for developers and data analytics to build a machine learning model with data in MongoDB.PyMongo is one of the great libraries which is used to embed MongoDB syntax into python code. All methods and functions of MongoDB can be imported to be used in machine learning.

MongoDB is a query language where developers can build an application that can be analyzed in multiple dimensions. Data can be easily accessed by single keys, ranges, text, and geospatial queries. It also provides pipeline and Mapreduce features.

MongoDB allows to reduce training time for the models and makes it a scalable database layer.MongoDB also offers to maximize the output and minimize the latency of the machine learning.

Conclusion

MongoDB gives the flexibilities and capabilities such as flexible data model, Query models, Data models, and its easy access to the data where data can be tuned easily and have consistency to make training. It also allows using of Machine learning algorithms much easier rather than using traditional and relational databases.