Computational Linguistics and Natural Language Processing (NLP)
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Computational Linguistics: Models, Resources, Applications
This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). It will be of interest and practical use to a wide range of linguists. Speech and Language Processing (Dan Jurafsky, et al)
This text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. It describes a unified vision of speech and language processing. Emphasis is on practical and scientific applications. Mathematical Linguistics (Andras Kornai)
This book introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing (NLP). It presents linguistics as a cumulative body of knowledge from the ground up. O'Reilly® Natural Language Processing with Python
This book offers a highly accessible introduction to natural language processing (NLP), the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.
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$12, 775 for 1 yr full-time - Commonwealth Supported Place (HECS) Learn more about fees. The tuition fees you pay will depend on the units you choose to study as each unit has its own costs. The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students undertaking the first year of this course. The cost will vary depending on the units you choose, your study load, the time it takes to complete your course and any approved Recognition of Prior Learning you have. Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together 8 credit points of a typical combination of units for that course. Eight credit points is used as it represents a typical full-time enrolment load for a year. You can find the credit point value of each unit under the Unit Description by searching for the unit in the Handbook. Learn more about fees and available payment options. Scholarship options
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Another trait which lawyers should have is intelligence. Having this positive attribute will ensure that the person representing the client is one who is smart enough to know what to do, when to do it and how to go about getting the results which are necessary to win the case and/or abide by the client's wishes. A lawyer who uses their brain is more likely to see the best possible outcome from a case. It can arguably be said that those who become lawyers are individuals who like to read. The legal profession is filled with volumes of laws, regulations, cases and rules. If one does not favor reading, then becoming a lawyer may not be the best bet, as the legal field is one which requires massive amounts of reading. Good comprehension skills are another favorable trait which all lawyers should have. Although one who likes to read may be a candidate for the legal profession, this in and of itself means nothing if the person reading does not comprehend that which they just read. Statutes and procedural rules are difficult to understand at times and those who have good comprehension skills may prosper at being a lawyer as they will have to read the pertinent documentation much less than those without good comprehension skills.
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