October 31, 2020 Classification, Data Science, Intermediate, NLP, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

6 Practices to enhance the performance of a Text Classification Model

Introduction A few months back, I was working on creating a sentiment classifier for Twitter data. After trying the common approaches, I was still struggling to get good accuracy on the results. Text classification problems and algorithms have been around for a while now. They are widely used for Email Spam Filtering by the likes of Google and Yahoo, for conducting sentiment analysis of twitter data and automatic news categorization in google alerts. However, while dealing with enormous amount of text […]

October 31, 2020 Intermediate, Libraries, Machine Learning, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Extracting information from reports using Regular Expressions Library in Python

Introduction Many times it is necessary to extract key information from reports, articles, papers, etc. For example names of companies – prices from financial reports, names of judges – jurisdiction from court judgments, account numbers from customer complaints, etc. These extractions are part of Text Mining and are essential in converting unstructured data to a structured form which are later used for applying analytics/machine learning. Such entity extraction uses approaches like ‘lookup’, ‘rules’ and ‘statistical/machine learning’. In ‘lookup’ based approaches, […]

October 31, 2020 Advanced, Algorithm, Deep Learning, NLP, Python, Sequence Modeling, Supervised Leave a comment

Essentials of Deep Learning : Introduction to Long Short Term Memory

Introduction Sequence prediction problems have been around for a long time. They are considered as one of the hardest problems to solve in the data science industry. These include a wide range of problems; from predicting sales to finding patterns in stock markets’ data, from understanding movie plots to recognizing your way of speech, from language translations to predicting your next word on your iPhone’s keyboard. With the recent breakthroughs that have been happening in data science, it is found […]

October 31, 2020 Advanced, Algorithm, Business Analytics, Deep Learning, NLP Leave a comment

Replicating Human Memory Structures in Neural Networks to Create Precise NLU algorithms

Introduction Machine learning and Artificial Intelligence developments are happening at breakneck speed! At such pace, you need to understand the developments at multiple levels – you obviously need to understand the underlying tools and techniques, but you also need to develop an intuitive understanding of what is happening. By the end of this article, you will develop an intuitive understanding of RNNs, especially LSTM & GRU. Ready? Let’s go! Table of Contents Simple exercise – Tweet classification How does […]

October 31, 2020 Classification, Data Science, Intermediate, NLP, Project, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

An NLP Approach to Mining Online Reviews using Topic Modeling (with Python codes)

Introduction E-commerce has revolutionized the way we shop. That phone you’ve been saving up to buy for months? It’s just a search and a few clicks away. Items are delivered within a matter of days (sometimes even the next day!). For online retailers, there are no constraints related to inventory management or space management They can sell as many different products as they want. Brick and mortar stores can keep only a limited number of products due to the finite space […]

October 31, 2020 Deep Learning, Intermediate, Libraries, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Introduction to StanfordNLP: An Incredible State-of-the-Art NLP Library for 53 Languages (with Python code)

Introduction A common challenge I came across while learning Natural Language Processing (NLP) – can we build models for non-English languages? The answer has been no for quite a long time. Each language has its own grammatical patterns and linguistic nuances. And there just aren’t many datasets available in other languages. That’s where Stanford’s latest NLP library steps in – StanfordNLP. I could barely contain my excitement when I read the news last week. The authors claimed StanfordNLP could support more […]

October 31, 2020 Advanced, E-Commerce, NLP, Project, Python, Recommendation, Structured Data, Technique, Unsupervised Leave a comment

Building a Recommendation System using Word2vec: A Unique Tutorial with Case Study in Python

Overview Recommendation engines are ubiquitous nowadays and data scientists are expected to know how to build one Word2vec is an ultra-popular word embeddings used for performing a variety of NLP tasks We will use word2vec to build our own recommendation system. Curious how NLP and recommendation engines combine? Let’s find out! Introduction Be honest – how many times have you used the ‘Recommended for you’ section on Amazon? Ever since I found out a few years back that machine […]

October 31, 2020 Advanced, Algorithm, Computer Vision, Deep Learning, NLP, Python, Unstructured Data Leave a comment

A Comprehensive Guide to Attention Mechanism in Deep Learning for Everyone

Overview The attention mechanism has changed the way we work with deep learning algorithms Fields like Natural Language Processing (NLP) and even Computer Vision have been revolutionized by the attention mechanism We will learn how this attention mechanism works in deep learning, and even implement it in Python Introduction “Every once in a while, a revolutionary product comes along that changes everything.” – Steve Jobs What does one of the most famous quotes of the 21st century have to do with […]

October 31, 2020 Intermediate, NLP, Python, Technique, Unsupervised, Word Embeddings Leave a comment

An Essential Guide to Pretrained Word Embeddings for NLP Practitioners

Overview Understand the importance of pretrained word embeddings Learn about the two popular types of pretrained word embeddings – Word2Vec and GloVe Compare the performance of pretrained word embeddings and learning embeddings from scratch Introduction How do we make machines understand text data? We know that machines are supremely adept at dealing and working with numerical data but they become sputtering instruments if we feed raw text data to them. The idea is to create a representation of words […]

October 31, 2020 Beginner, NLP, Python, Technique, Unstructured Data Leave a comment

How Part-of-Speech Tag, Dependency and Constituency Parsing Aid In Understanding Text Data?

Overview Learn about Part-of-Speech (POS) Tagging, Understand Dependency Parsing and Constituency Parsing Introduction Knowledge of languages is the doorway to wisdom. – Roger Bacon I was amazed that Roger Bacon gave the above quote in the 13th century, and it still holds, Isn’t it? I am sure that […]

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