archives

Let’s face it. Data is scattered all over the place in silos in an enterprise. Starting from email server, intranet, countless documents, reports, presentations, charts/graphs in various document repositories, ERP, internal systems, e.g. HRIS, databases, source code control system, release repositories, wikis, ticketing system etc., we can keep going and find how data is distributed […]

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To give some pretext of my background I come from a programming background. When a program does not give the desired result I could ‘debug the program’. I could add breakpoints in the code, watch variables as they change, stop the program at a breakpoint and inspect the ‘state’ so to say and figure out […]

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With the advent of chatbots, training computers to read, understand and write language has become a big business. The training may seem easy at first but as you start your journey with Natural Language Processing (NLP) you realize that surmounting the challenges is no easy task. That’s why sentence similarity is amongst the toughest problems. […]

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There are many existing out-of-box NLP models available today. These can take a sentence and match it with a list of available sentences and pick the top matches from them. However, they make basic assumptions about the sentence structure or words in them. Those may not apply necessarily to a chatbot conversation. Let’s find out […]

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Conversations between a human and a chatbot have a distinct style. Typically humans use short phrases, short sentences, sometimes just a single word, question like sentence, with or without proper context and lowercase in most cases when seeking answers from a chatbot. This is where we talk about NLP implementations in chatbots. NLP implementations in […]

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Natural Language Understanding or NLU is a subtopic within NLP that should focus on deriving the meaning of a sentence in a conversation with a chatbot, determine the context of the conversation, predict the intent of the user and obtain word level metadata. NLU should employ reading comprehension techniques to process text data to extract […]

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Let us consider the steps followed for using a scientific method to study and understand the natural world. Then we can attempt to do the same to study and understand data science. Scientific Method Typically, scientists undertake the following steps when they want to explore the natural world. Define Objective Here is when you get […]

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The term “Data Science”, the modern version, was coined in 2008.  It has ever since taken the world by storm! Revolutionary as the idea is, it has, quite understandably, created some confusion too. Moreover, it encompasses such a broad area that if you ask ten people what it means you may be discovering ten completely […]

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In part 1, we discussed the importance of chatbots in the enterprise and what it takes to make chatbots enterprise ready. We will continue the discussion in this blog. Customisations for enterprise Human – Machine interaction has never been easy. Humans want to interact with machines in the same way they interact with other humans […]

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Enterprises are slowly waking up to chatbots and hence, enterprise chatbots are coming in the big picture. Chatbots are going to be crucial tomorrow for engaging various constituencies, candidates and hires, employees, vendors and consultants. Chatbots are here to stay Initial applications in the consumer space from Apple, Microsoft, Amazon and google are going too mainstream. If […]

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