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The Future in : ML and NLP

Machine   learning  is    a  core  sub-area  of    artificial  intelligence   (AI) 

that   provides  system,  the ability to automatically  learn and  improve 

from    experience    without   being  explicitly   programmed.   Machine

learning  focuses  on    the  development  of  computer  programs   that

can  access   data   and  use   it  learn for themselves.  With the constant

evolution of the field, it has  become the most relevant   technoloigical

breakthrough  of  recent  time.  Yet,   Lack  of   expert resources   is  the 

biggest challenge  the  world  is   facing.  Natural  Language  Processing

or   Computational   Linguistics   (NLP / CL)  is   a  subfield    of   Artificial 

Intelligence  that   is   one  of  the most    relevant technologies  of   the 

Digital Age. 

While natural language processing isn’t a new science, the technology is rapidly advancing due to an increased interest in human to machine communications, availability of big data, powerful computing and enhanced algorithms. NLP systems can perform many useful tasks such as extracting knowledge from text, machine translation and conversational agents, by analyzing and manipulating language . The objective of  the winter school is to introduce the basic background in NLP and relevant ML methods as well as to introduce them to some exhilarating research in this area. 

Eminent speakers from academia as well as industry will deliver talks and will interact with the students.   ICFOSS seeks to establish a platform to endorse the research activities in the area and to expand the skills of the participants through the programme . We intent to promote and support the involvement of women in FOSS communities as well as in the field of Natural Language Processing (NLP). The event includes invited talks and hands-on sessions and provide an opportunity for the participants to acquire individual attention of mentors and to develop network between themselves. The school shall focus to provide hands-on experience to boost the capability and potential of the participants. The course will present the basic NLP problems such as Part-Of-Speech Tagging and Named Entity Recognition and will pay attention to some approaches for Speech Recognition, Speech Synthesis and Machine Translation . The practical part of the course includes working with NLTK, gensim, scikit-learn, NumPy, spaCy, and SciPy for solving these problems. Programming skills are welcome, but not strongly required. We will render introductory knowledge of Python to help the participant s in doing their computations on their own, while taking in account to each of their individual skills and interests.