I recently completed a course on NLP through Deep Learning (CS224N) at Stanford and loved the experience. Learnt a whole bunch of new things. For my final project I worked on a question answering model built on Stanford Question Answering Dataset (SQuAD). In this blog, I want to cover the main building blocks of a question answering model.
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I decided to give myself the challenge of seeing if I could teach a machine learning model to detect the difference between Onion articles (and other satire) and real news articles in less than an hour.
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I still learn new knowledge everyday with my growing passion in Data Science field. To pursue different career track as a graduating physics student there must be 'Why' and 'How' questions to be answered.
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Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. About half of data professionals said they were competent in supervised machine learning (49%) and logistic regression (53%).
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A recent survey of over 16,000 data professionals showed that the most used platforms/resources included Kaggle, Online courses and Stack Overflow Q&A. Additionally, the most useful platforms/resources included Personal Projects, Online courses and Stack Overflow Q&A.
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As digital marketing strategies grow more sophisticated and complex, businesses find themselves wrestling with more data than ever.
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The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. For more information about this 700+ pages free book and its authors, click here.
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Data scientists work at all levels of the organization. Our survey of data professionals revealed that Director-level data scientists have the highest level of proficiency across many data science skills and work with more of their peers compared to data scientists who are Individual Contributors, Managers or even Executives. Satisfaction with outcome of analytics projects did not differ across job levels.
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