archives

Understanding Face Recognition Algorithms Introduction Building a robust Face Recognition system that is free of bias (racial or gender), is not an easy task. Algorithms don’t create bias. It comes from humans. The last decade was full of new state-of-the-art algorithms and groundbreaking research in the field of Deep Learning. New Computer vision algorithms were […]

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In the world of deep learning AI model, ‘Bigger is Better’ is the norm. Which means bigger models perform better. Earlier this year NVIDIA announced the MegatronLM – a monster language model that packs 8.3 billion parameters inside the model. The parameters occupy 33 GB disk space.  512 V100 GPUs ran continuously for more than […]

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In 2019 the total number of Deep learning research papers published in arxiv.org is more than 8000. Deep Learning has solved hard problems such as language translation and cancer detection with very good results. Jobs in deep learning are the most sought after by people who want to build a career in Data Science. Kai-Fu-Lee […]

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Chatbots have become a very popular medium To ask questions, access data and share information using Natural Language we now have chatbots. Most of us have had experiences with chatbots in our daily lives to perform simple tasks quickly and in our own convenient time. However, adoption of chatbots to access data within an enterprise, […]

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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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