Build an end-end Currency Convertor chatbot with Python and Dialogflow

This article was published as a part of the Data Science Blogathon Introduction Hello all, Hope you are fine. In this tutorial we will learn how to create chatbots using Dialogflow and python, as well we will learn the deployment of chatbots to telegram. In our previous articles, we have learned to create a simple rule-based chatbot using simple python and NLTK libraries. I would like to request you to have a look at the article creating a simple chatbot […]

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Regex Cheatsheet For Natural Language Processing tasks

This article was published as a part of the Data Science Blogathon Introduction Regex is a shorthand for Regular Expression. It is a representation for a set, a set of strings. Say we have a list of emails and we want to check if they are in the correct format or not. One way is to check each and every mail manually but that’s not possible if the number of mails is quite high. So, regex here comes to your rescue. […]

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Amazon Product review Sentiment Analysis using BERT

This article was published as a part of the Data Science Blogathon Introduction Natural Language processing, a sub-field of machine learning has gained immense popularity in the last 5 years in both research and industrial applications due to the advancement in the field of deep learning and improvement in the computational power of hardware systems. It is a technique for computers to understand how human languages work involving the usage of computational linguistics and the computer science domain. In recent years, […]

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TS-SS similarity for Answer Retrieval from Document in Python

This article was published as a part of the Data Science Blogathon Introduction This article focuses on answer retrieval from a document by using a similarity algorithm. This task falls under Natural Language Processing which is a subset of Deep Learning. In this article, we will be understanding why do we require better techniques and what are the drawbacks of using naive algorithms. Moreover, we will be implementing a similarity-based technique for answer retrieval from the document. This article is a […]

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Step by step guide to building sentiment analysis model using graphlab

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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Natural Language Processing Made Easy – using SpaCy (​in Python)

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 – text classification, entity detection, machine translation, question […]

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Introduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library

Introduction Last couple of years have been incredible for Natural Language Processing (NLP) as a domain! We have seen multiple breakthroughs – ULMFiT, ELMo, Facebook’s PyText, Google’s 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. What’s 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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How to use a Machine Learning Model to Make Predictions on Streaming Data using PySpark

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 We’ll cover the basics of Streaming Data and Spark Streaming, and then dive into the implementation part   Introduction Picture this – 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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How to build your first Machine Learning model on iPhone (Intro to Apple’s CoreML)

Introduction The data scientist in me is living a dream – I can see top tech companies coming out with products close to the area I work on. If you saw the recent Apple iPhone X launch event, iPhone X comes with some really cool features like FaceID, Animoji, Augmented Reality out of box, which use the power of machine learning. The hacker in me wanted to get my hands dirty and figure out what it takes to build a system like […]

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Introduction to PyTorch-Transformers: An Incredible Library for State-of-the-Art NLP (with Python code)

Overview We look at the latest state-of-the-art NLP library in this article called PyTorch-Transformers We will also implement PyTorch-Transformers in Python using popular NLP models like Google’s BERT and OpenAI’s GPT-2! This has the potential to revolutionize the landscape of NLP as we know it   Introduction “NLP’s ImageNet moment has arrived.” – Sebastian Ruder Imagine having the power to build the Natural Language Processing (NLP) model that powers Google Translate. What if I told you this can be done […]

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