Python tutorials

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 […]

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

Simple Text Multi Classification Task Using Keras BERT

This article was published as a part of the Data Science Blogathon. Introduction BERT is a really powerful language representation model that has been a big milestone in the field of NLP. It has greatly increased our capacity to do transfer learning in NLP. It comes with great promise to solve a wide variety of NLP tasks. Definitely you will gain great knowledge by the end of this article, keep reading. I am sure you will get good hands-on experience […]

October 29, 2020 Clustering, Libraries, Machine Learning, NLP, Programming, Python, Technique, Text, Unstructured Data, Unsupervised Leave a comment

Introductory guide to Information Retrieval using kNN and KDTree

Introduction I love cricket as much as I love data science. A few years back (on 16 November 2013 to be precise), my favorite cricketer – Sachin Tendulkar retired from International Cricket. I spent that entire day reading articles and blogs about him on the web. By the end of the day, I had read close to 50 articles about him. Interestingly, while I was reading these articles – none of the websites suggested me articles outside of Sachin or cricket. […]

October 29, 2020 Deep Learning, Image, NLP, Project, Python, PyTorch, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

Automatic Image Captioning using Deep Learning (CNN and LSTM) in PyTorch

Introduction Deep Learning is a very rampant field right now – with so many applications coming out day by day. And the best way to get deeper into Deep Learning is to get hands-on with it. Take up as much projects as you can, and try to do them on your own. This would help you grasp the topics in more depth and assist you in becoming a better Deep Learning practitioner. In this article, we will take a look […]

October 29, 2020 Advanced, Deep Learning, NLP, Project, Python, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

A Must-Read NLP Tutorial on Neural Machine Translation – The Technique Powering Google Translate

Introduction “If you talk to a man in a language he understands, that goes to his head. If you talk to him in his own language, that goes to his heart.” – Nelson Mandela The beauty of language transcends boundaries and cultures. Learning a language other than our mother tongue is a huge advantage. But the path to bilingualism, or multilingualism, can often be a long, never-ending one. There are so many little nuances that we get lost in the […]

October 29, 2020 Algorithm, Intermediate, NLP, Python, Sequence Modeling, Supervised, Text, Unstructured Data Leave a comment

OpenAI’s GPT-2: A Simple Guide to Build the World’s Most Advanced Text Generator in Python

Overview Learn how to build your own text generator in Python using OpenAI’s GPT-2 framework GPT-2 is a state-of-the-art NLP framework – a truly incredible breakthrough We will learn how it works and then implements our own text generator using GPT-2 Introduction “The world’s best economies are directly linked to a culture of encouragement and positive feedback.” Can you guess who said that? It wasn’t a President or Prime Minister. It certainly wasn’t a leading economist like Raghuram Rajan. […]

October 29, 2020 Computer Vision, Data Visualization, Github, Graphs & Networks, Intermediate, Listicle, NLP, Python Leave a comment

6 Exciting Open Source Data Science Projects you Should Start Working on Today

Overview Here are six open-source data science projects to enhance your skillset These projects cover a diverse set of domains, from computer vision to natural language processing (NLP), among others Pick your favorite open-source data science project(s) and get coding! Introduction I recently helped out in a round of interviews for an open data scientist position. As you can imagine, there were candidates from all kinds of backgrounds – software engineering, learning and development, finance, marketing, etc. What stood […]

October 29, 2020 Beginner, Libraries, NLP, Python, Technique, Text, Unstructured Data Leave a comment

spaCy Tutorial to Learn and Master Natural Language Processing (NLP)

Introduction spaCy is my go-to library for Natural Language Processing (NLP) tasks. I’d venture to say that’s the case for the majority of NLP experts out there! Among the plethora of NLP libraries these days, spaCy really does stand out on its own. If you’ve used spaCy for NLP, you’ll know exactly what I’m talking about. And if you’re new to the power of spaCy, you’re about to be enthralled by how multi-functional and flexible this library is. The factors […]

October 29, 2020 Advanced, Call Center, NLP, Python, Structured Data Leave a comment

NLP Applications in Support Call Centers

This article was published as a part of the Data Science Blogathon. Introduction This article is in continuation of my previous article on using Machine learning in Support environments. I shared my views on, how using simple python code we can enrich our call centers/support division activities in our own organization or customer organization. In that article, I shared an insight into what and how we can make a difference to the current environment using ML in giving better service […]

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