Category: Supervised

Intermediate, NLP, Project, Python, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

A Guide to Building an Intelligent Chatbot for Slack using Dialogflow API

Introduction Breakthroughs in the field of Natural Language Processing (NLP) have seen a sudden rise in recent times. The amount of text data available to us is enormous, and data scientists are coming up with new and innovative solutions to parse through it and analyse patterns. From writing entire novels to decoding ancient texts, we have seen a variety of applications for NLP. One of the most popular applications is a chatbot. Organizations like Zomato, Starbucks, Lyft, and Spotify are leveraging […]

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Classification, Computer Vision, Deep Learning, Image, Libraries, NLP, Programming, Python, PyTorch, Supervised, Unstructured Data Leave a comment

Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

Introduction PyTorch v TensorFlow – how many times have you seen this polarizing question pop up on social media? The rise of deep learning in recent times has been fuelled by the popularity of these frameworks. There are staunch supporters of both, but a clear winner has started to emerge in the last year. PyTorch was one of the most popular frameworks in 2018. It quickly became the preferred go-to deep learning framework among researchers in both academia and the […]

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Classification, Machine Learning, NLP, Project, Python, Supervised, Technique, Telecom, Text, Unstructured Data Leave a comment

Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification

Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started exploring possibilities of transforming this idea into a Natural Language Processing (NLP) problem. That article showcases computer vision techniques to predict a movie’s genre. So I had to find a way to convert that problem statement into text-based data. Now, most NLP tutorials look at solving single-label classification challenges (when there’s only one label per observation). […]

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Beginner, Classification, Deep Learning, NLP, Project, Python, PyTorch, Supervised, Technique, Text, Unstructured Data Leave a comment

Build Your First Text Classification model using PyTorch

Overview Learn how to perform text classification using PyTorch Grasp the importance of Pack Padding feature Understand the key points involved while solving text classification Introduction I always turn to State of the Art architectures to make my first submission in data science hackathons. Implementing the State of the Art architectures has become quite easy thanks to deep learning frameworks such as PyTorch, Keras, and TensorFlow. These frameworks provide an easy way to implement complex model architectures and algorithms with […]

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Classification, Data Science, Intermediate, NLP, Project, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

Sentiment Analysis of Twitter Posts on Chennai Floods using Python

Introduction The best way to learn data science is to do data science. No second thought about it! One of the ways, I do this is continuously look for interesting work done by other community members. Once I understand the project, I do / improve the project on my own. Honestly, I can’t think of a better way to learn data science. As part of my search, I came across a study on sentiment analysis of Chennai Floods on Analytics Vidhya. […]

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Algorithm, Deep Learning, Intermediate, NLP, Supervised, Text, Unstructured Data Leave a comment

A Simple Introduction to Sequence to Sequence Models

Overview In this article, I would give you an overview of sequence to sequence models which became quite popular for different tasks like machine translation, video captioning, image captioning, question answering, etc. Prerequisites: The reader should already be familiar with neural networks and, in particular, recurrent neural networks (RNNs). In addition, knowledge of LSTM or GRU models is preferable. If you are not familiar with LSTM I would prefer you to read LSTM- Long Short-Term Memory.

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