figure - constituency parse tree for our sample sentence thus you can clearly see that figure - depicts the constituency grammar based parse tree for our sample sentencewhich consists of multiple noun phrases (npeach phrase has several words that are also annotated with their own parts of speech (postags we cover more on processing and analyzing textual data for various steps in the machine learning pipeline as well as practical use cases in subsequent eep learning the field of deep learningas depicted earlieris sub-field of machine learning that has recently come into much prominence its main objective is to get machine learning research closer to its true goal of "making machines intelligentdeep learning is often termed as rebranded fancy term for neural networks this is true to some extent but there is definitely more to deep learning than just basic neural networks deep learning based algorithms involves the use of concepts from representation learning where various representations of the data are learned in different layers that also aid in automated feature extraction from the data in simple termsa deep learning based approach tries to build machine intelligence by representing data as layered hierarchy of conceptswhere each layer of concepts is built from other simpler layers this layered architecture itself is one of the core components of any deep learning algorithm in any basic supervised machine learning techniquewe basically try to learn mapping between our data samples and our output and then try to predict output for newer data samples representational learning tries to understand the representations in the data itself besides learning mapping from inputs to outputs this makes deep learning algorithms extremely powerful as compared to regular techniqueswhich require significant expertise in areas like feature extraction and engineering deep learning is also extremely effective with regard to its performance as well as scalability with more and more data as compared to older machine learning algorithms this is depicted in figure - based on slide from andrew ng' talk at the extract data conference