September 25, 2020 Python

Python for NLP: Deep Learning Text Generation with Keras

This is the 21st article in my series of articles on Python for NLP. In the previous article, I explained how to use Facebook’s FastText library for finding semantic similarity and to perform text classification. In this article, you will see how to generate text via deep learning technique in Python using the Keras library. Text generation is one of the state-of-the-art applications of NLP. Deep learning techniques are being used for a variety of text generation tasks such as […]

September 25, 2020 Python

Python for NLP: Neural Machine Translation with Seq2Seq in Keras

This is the 22nd article in my series of articles on Python for NLP. In one of my previous articles on solving sequence problems with Keras, I explained how to solve many to many sequence problems where both inputs and outputs are divided over multiple time-steps. The seq2seq architecture is a type of many-to-many sequence modeling, and is commonly used for a variety of tasks such as Text-Summarization, chatbot development, conversational modeling, and neural machine translation, etc. In this article, […]

September 25, 2020 Python

Removing Stop Words from Strings in Python

In this article, you are going to see different techniques for removing stop words from strings in Python. Stop words are those words in natural language that have a very little meaning, such as “is”, “an”, “the”, etc. Search engines and other enterprise indexing platforms often filter the stop words while fetching results from the database against the user queries. Stop words are often removed from the text before training deep learning and machine learning models since stop words occur […]

September 25, 2020 Based

Recommender Engine – Under The Hood

Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger. There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them. Content based: In content based recommender systems, keywords […]

September 21, 2020 Python Leave a comment

Text Classification with Python and Scikit-Learn

Introduction Text classification is one of the most important tasks in Natural Language Processing. It is the process of classifying text strings or documents into different categories, depending upon the contents of the strings. Text classification has a variety of applications, such as detecting user sentiment from a tweet, classifying an email as spam or ham, classifying blog posts into different categories, automatic tagging of customer queries, and so on. In this article, we will see a real-world example of […]

September 21, 2020 Python Leave a comment

Text Summarization with NLTK in Python

Introduction As I write this article, 1,907,223,370 websites are active on the internet and 2,722,460 emails are being sent per second. This is an unbelievably huge amount of data. It is impossible for a user to get insights from such huge volumes of data. Furthermore, a large portion of this data is either redundant or doesn’t contain much useful information. The most efficient way to get access to the most important parts of the data, without having to sift through […]

September 21, 2020 Python Leave a comment

Implementing Word2Vec with Gensim Library in Python

Introduction Humans have a natural ability to understand what other people are saying and what to say in response. This ability is developed by consistently interacting with other people and the society over many years. The language plays a very important role in how humans interact. Languages that humans use for interaction are called natural languages. The rules of various natural languages are different. However, there is one thing in common in natural languages: flexibility and evolution. Natural languages are […]

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