nltk or natural language toolkit--as the name suggestsits focus is working with natural language it' an extensive library that comes bundled with number of text corpuses to help you model your own data pylearn --another machine learning toolbox but bit less mature than scikit-learn tensorflow-- python library for deep learning provided by google the landscape doesn' end with python librariesof course spark is new apachelicensed machine-learning enginespecializing in real-learn-time machine learning it' worth taking look at and you can read more about it at nosql databases if you need to store huge amounts of datayou require software that' specialized in managing and querying this data traditionally this has been the playing field of relational databases such as oracle sqlmysqlsybase iqand others while they're still the go-to technology for many use casesnew types of databases have emerged under the grouping of nosql databases the name of this group can be misleadingas "noin this context stands for "not only lack of functionality in sql isn' the biggest reason for the paradigm shiftand many of the nosql databases have implemented version of sql themselves but traditional databases had shortcomings that didn' allow them to scale well by solving several of the problems of traditional databasesnosql databases allow for virtually endless growth of data these shortcomings relate to every property of big datatheir storage or processing power can' scale beyond single node and they have no way to handle streaminggraphor unstructured forms of data many different types of databases have arisenbut they can be categorized into the following typescolumn databases--data is stored in columnswhich allows algorithms to perform much faster queries newer technologies use cell-wise storage table-like structures are still important document stores--document stores no longer use tablesbut store every observation in document this allows for much more flexible data scheme streaming data--data is collectedtransformedand aggregated not in batches but in real time although we've categorized it here as database to help you in tool selectionit' more particular type of problem that drove creation of technologies such as storm key-value stores--data isn' stored in tablerather you assign key for every valuesuch as org marketing sales this scales well but places almost all the implementation on the developer sql on hadoop--batch queries on hadoop are in sql-like language that uses the map-reduce framework in the background new sql --this class combines the scalability of nosql databases with the advantages of relational databases they all have sql interface and relational data model