Ardent Python programmer.
Work with PyTorch, Tensorflow and Numpy to design and implement Deep Learning modules.
Skilled with Gensim and Fasttext.
Keen interest in Meta-Cognition and Neuro-Computations.Describe what you have done, what you are doing, and the kinds of things you are interested in.
-> Deep Learning:
Recurrent Neural Networks, Convolutional Neural Networks, Transfer Learning, Deep Generative Models, Attention Networks, Self-Attention Networks, Encoder-Decoder, Auto-Encoder etc
Word2Vec (SkipGram & CBOW), Sense2Vec, Doc2Vec, ThoughtVector, Glove, HybridVectors (own)
-> Neuro-Science / Reinforcement-Learning Architecture:
Neocortex (Hierarchical Temporal Memory), Medial Prefrontal Cortex (multi-tier reward process [CPP, ICSS]), Anterior Prefrontal Cortex (complex cognitive behaviours & personality expression), Brodmann areas in Cerebrum
PyTorch, Tensorflow, Theano, Keras, NumPy, SciPy, Spacy, Scikit-Learn, Gensim, Stanford-CoreNLP, Fasttext
Semantic Relatedness, Recommendation Systems, Topic Modelling, Opinion Mining, Text Summarisation, User Profiling, Dynamic Text Tag Generation etc.