**Table 11:** Deep learning algorithms used on big data.

Algorithms |
Description of the algorithms |
No of FS Applied |

CNN | Convolutional Neural Networks | [FS4], [FS7], [FS8], [FS13], [FS21], [FS29], [FS30], [FS32], [FS16], [FS19], [F5], [F10], [F23] |

DNN | Deep neural networks | [FS8], [FS13], [FS15], [FS22], [FS25], [FS27], [FS26], [FS14] |

DBN | Deep Belief Networks | [FS20], [FS6], [FS24], [FS31] |

DCNN | Deep Convolutional Neural Networks | [FS33], [FS25], [FS23] |

RNN | Recurrent Neural Networks | [FS13], [FS28], [FS7], [FS5], [FS18] |

C-RNN | Convolutional-recursive neural network | [FS18] |

RCNN | Region-based Convolutional Network | [FS3], [F29] |

ELM, H-ELM | Extreme learning and hierarchical extreme learning | [FS2] |

LEML | Metric learning method to learn | [FS4] |

MDB | Spark-based Deep Learning Framework for MBD Analytics | [FS11] |

H2O Deep Learning | Deep learning with H2O features | [FS12] |

TDML | TENSOR DEEP LEARNING MODEL | [FS17] |

DCH | Deep concept hierarchies | [FS18] |