Deep Learning, NLP, NMT, AI, ML
Introduction News media has become a channel to pass on the information of whatâs happening in the world to the people living. Often people perceive whatever conveyed in the news to be true. There were circumstances where even the news channels acknowledged that their news is not true as they wrote. But some news has a significant impact not only on the people or
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This article was published as a part of the Data Science Blogathon. Background I wonât be lying if I assert that every developer/engineer/student has used the website Stack Overflow more than once in their journey. Widely considered as one of the largest and more trusted websites for developers to learn and share their knowledge, the website presently hosts in excess of 10,000,000 questions. In this post, we try to predict the question tags based on the question text asked on […]
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Text Mining is one of the most complex analysis in the industry of analytics. The reason for this is that, while doing text mining, we deal with unstructured data. We do not have clearly defined observation and variables (rows and columns). Hence, for doing any kind of analytics, you need to first convert this unstructured data into a structured dataset and then proceed with normal modelling framework. The additional step of converting an unstructured data into a structured format is […]
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I have been using graph lab for quite some time now. The first Kaggle competition I used it for was Click Trough Rate (CTR) and I was amazed to see the speed at which it can crunch such big data. Over last few months, I have realised much broader applications of GraphLab. In this article I will take up the text mining capability of GraphLab and solve one of the Kaggle problems. I will be referring to this problem with […]
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Introduction Natural Language Processing is one of the principal areas of Artificial Intelligence. NLP plays a critical role in many intelligent applications such as automated chat bots, article summarizers, multi-lingual translation and opinion identification from data. Every industry which exploits NLP to make sense of unstructured text data, not just demands accuracy, but also swiftness in obtaining results. Natural Language Processing is a capacious field, some of the tasks in nlp are â text classification, entity detection, machine translation, question […]
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Introduction What do we do when we need any information? Simple: âWe Ask, and Google Tellsâ. But if the answer depends on multiple variables, then the existing Ask-Tell model tends to sputter. State of the art search engines usually cannot handle such requests. We would have to search for information available in bits and pieces and then try to filter and assemble relevant parts together. Sounds time consuming, doesnât it? Source: Inbenta This Ask-Tell model is evolving rapidly with the […]
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Improving Text Classification Models While the above framework can be applied to a number of text classification problems, but to achieve a good accuracy some improvements can be done in the overall framework. For example, following are some tips to improve the performance of text classification models and this framework. 1. Text Cleaning : text cleaning can help to reducue the noise present in text data in the form of stopwords, punctuations marks, suffix variations etc. This article can help to understand how […]
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Introduction Last couple of years have been incredible for Natural Language Processing (NLP) as a domain! We have seen multiple breakthroughs â ULMFiT, ELMo, Facebookâs PyText, Googleâs BERT, among many others. These have rapidly accelerated the state-of-the-art research in NLP (and language modeling, in particular). We can now predict the next sentence, given a sequence of preceding words. Whatâs even more important is that machines are now beginning to understand the key element that had eluded them for long. Context! Understanding context […]
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Overview Streaming data is a thriving concept in the machine learning space Learn how to use a machine learning model (such as logistic regression) to make predictions on streaming data using PySpark Weâll cover the basics of Streaming Data and Spark Streaming, and then dive into the implementation part  Introduction Picture this â every second, more than 8,500 Tweets are sent, more than 900 photos are uploaded on Instagram, more than 4,200 Skype calls are made, more than 78,000 […]
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The Importance of Exploratory Data Analysis (EDA) There are no shortcuts in a machine learning project lifecycle. We canât simply skip to the model building stage after gathering the data. We need to plan our approach in a structured manner and the exploratory data analytics (EDA) stage plays a huge part in that. I can say this with the benefit of hindsight having personally gone through this situation plenty of times. In my early days in this field, I couldnât […]
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