|Monday||11-13||N1, Polo Fibonacci|
|Tuesday||9-11||N1, Polo Fibonacci|
Forum on Piazza
Homework 2: deadline 6/11/2017.
The course targets text analytics systems and applications to respond to business problems by discovering and presenting knowledge that is otherwise locked in textual form. The objective is to learn to recognize situations in which text analytics techniques can solve information processing needs, to identify the analytic task/process that best models the business problem, to select the most appropriate resources methods and tools, to collect text data and apply such methods to them. Several applications context will be presented: information extraction, sentiment analysis (what is the nature of commentary on an issue), spam and fake posts detection, quantification problems, summarization, etc.
A server has been setup for running Jupyter Notebooks. In order to log into the server, you must get credentials for a Google Suite account:go to this page and register with your University credentials to activate your free account.
|19/9/2017||L'età della parola||L'età della parola|
|25/9/2017||Introduction to Probability||Probability|
|26/9/2017||Language Modeling||Language Modeling|
|2/10/2017||Introduction to Python 1/2||Python 1/2 (notebook)|
|3/10/2017||Introduction to Python 2/2||Python 2/2 (notebook, homework 1)|
|9/10/2017||Introduction to NLTK||Introduction to NLTK|
|10/10/2017||Basic Text Processing||Tokenization|
|16/10/2017||Word Similarity||Word Similarity|
|17/10/2017||Text Classification||Text Classification|
|23/10/2017||Hidden Markov Models||HMM|
|24/11/2017||Named Entity Recognition||NER.pptx|
|7/11/2017||Deep Learning for NLP||Deep Learning|
|13/11/2017||Neural Language Models||NLM (notebooks)|
|14/11/2017||Correction of Homework 2, Keras||Deep Leaning Libraries|