Deep Learning, NLP, NMT, AI, ML
This is how a word cloud of our entire website looks like! A word cloud is a graphical representation of frequently used words in a collection of text files. The height of each word in this picture is an indication of frequency of occurrence of the word in the entire text. By the end of this article, you will be able to make a word cloud using R on any given set of text files. Such diagrams are very useful when doing […]
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Introduction A few months back, I was working on creating a sentiment classifier for Twitter data. After trying the common approaches, I was still struggling to get good accuracy on the results. Text classification problems and algorithms have been around for a while now. They are widely used for Email Spam Filtering by the likes of Google and Yahoo, for conducting sentiment analysis of twitter data and automatic news categorization in google alerts. However, while dealing with enormous amount of text […]
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Introduction Many times it is necessary to extract key information from reports, articles, papers, etc. For example names of companies – prices from financial reports, names of judges – jurisdiction from court judgments, account numbers from customer complaints, etc. These extractions are part of Text Mining and are essential in converting unstructured data to a structured form which are later used for applying analytics/machine learning. Such entity extraction uses approaches like ‘lookup’, ‘rules’ and ‘statistical/machine learning’. In ‘lookup’ based approaches, […]
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Introduction E-commerce has revolutionized the way we shop. That phone you’ve been saving up to buy for months? It’s just a search and a few clicks away. Items are delivered within a matter of days (sometimes even the next day!). For online retailers, there are no constraints related to inventory management or space management They can sell as many different products as they want. Brick and mortar stores can keep only a limited number of products due to the finite space […]
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Introduction A common challenge I came across while learning Natural Language Processing (NLP) – can we build models for non-English languages? The answer has been no for quite a long time. Each language has its own grammatical patterns and linguistic nuances. And there just aren’t many datasets available in other languages. That’s where Stanford’s latest NLP library steps in – StanfordNLP. I could barely contain my excitement when I read the news last week. The authors claimed StanfordNLP could support more […]
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This article was published as a part of the Data Science Blogathon. Introduction BERT is a really powerful language representation model that has been a big milestone in the field of NLP. It has greatly increased our capacity to do transfer learning in NLP. It comes with great promise to solve a wide variety of NLP tasks. Definitely you will gain great knowledge by the end of this article, keep reading. I am sure you will get good hands-on experience […]
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Introduction Data science demands versatility. Move away from your regular methods, challenge your ways of working, explore new ways of doing things more efficiently. On reminiscing about my old days, my initial years in data science, I had also got trapped by this devil of ‘complacency’. At one point, I was not challenging myself enough. I wasn’t experimenting with the ways of doing work. I accepted the things as they were, until I realized ‘Complacency is a state of mind […]
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Introduction I love cricket as much as I love data science. A few years back (on 16 November 2013 to be precise), my favorite cricketer – Sachin Tendulkar retired from International Cricket. I spent that entire day reading articles and blogs about him on the web. By the end of the day, I had read close to 50 articles about him. Interestingly, while I was reading these articles – none of the websites suggested me articles outside of Sachin or cricket. […]
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Introduction Deep Learning is a very rampant field right now – with so many applications coming out day by day. And the best way to get deeper into Deep Learning is to get hands-on with it. Take up as much projects as you can, and try to do them on your own. This would help you grasp the topics in more depth and assist you in becoming a better Deep Learning practitioner. In this article, we will take a look […]
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Introduction “If you talk to a man in a language he understands, that goes to his head. If you talk to him in his own language, that goes to his heart.” – Nelson Mandela The beauty of language transcends boundaries and cultures. Learning a language other than our mother tongue is a huge advantage. But the path to bilingualism, or multilingualism, can often be a long, never-ending one. There are so many little nuances that we get lost in the […]
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