A comprehensive guide to unsupervised ML and the K-Means algorithm with a demo of a clustering use case for grouping image pixels by color — Unsupervised learning is a method in which underlying patterns in data can be discovered without providing extra information (or labels/targets) to a machine learning algorithm. …

A Brief Introduction to Vectorization and its Importance in the Context of NLP — Introduction Matrices and vectors are quantified information that Machine Learning(ML) algorithms require for learning patterns and making predictions. For applying these techniques to textual data as well, numeric representations of the texts are engineered to form matrices that hold the relevant information from those texts. …

Tracey Davis, the Founder & President of Money20/20 and the founder of the RiseUp initiative, opened the session of RiseUp Europe 2022 by quoting Kahina Van Dyke from Standard Chartered ~ The next chapter of banking and fintech will be so exciting — the most diverse and the most fun…

Explore how a text-based model’s performance could be improved by incorporating simple data and/or NLP techniques coupled with hyperparameter tuning for ANNs using KerasTuner’s Hyperband Algorithm — In my previous article on Multiclass Text Classification Using Keras to Predict Emotions, I compared the outcome of the usage of skipgrams to give a deep text classifier a headstart with learnt word embeddings for predicting emotions with that of another deep text classifier that learns the embeddings from scratch…

Learn Python’s useful built-in functions focusing on NLP use-cases — Beginner in Python & interested in Text Processing? Then read on… Natural Language Processing is in high demand now and Python has built-in functions to support whatever you need for processing and analyzing text. …

Disclaimer: This article is 90% generated using AI — Recently, I started digging into the HuggingFace library and thought of having some fun with the text generation pipeline. Hence, I wrote (… rather compiled) this interview-styled article About AI, by AI where I present a curation of texts that were generated with EleutherAI’s GPT Neo model using the questions…

Quick Scrape — Extract — Visualize — Analyze exercise using Pre-trained NLP models for Text Analytics — If you are working on a last-minute text analytics project, you are probably at the right place. The idea here is to apply text analysis techniques and analyze tweets that were posted on Earth Day, i.e. on the 22nd of April. I’ll start by narrating why I chose these libraries. …

Do word embeddings add value to text classification models? Let’s find out in this multiclass prediction task for detecting emotions — Introduction Word Embeddings in Natural Language Processing In Natural Language Expressions, similar words occur in similar contexts. For example, in this sentence — ‘I am not feeling well, I am sick. I probably had covid!’. The words — not-felling-well, sick, and covid are keywords that indicate that a person is sick…

A list of notebook extensions to make your Jupyter Notebook environment more productive, structured, and presentable — If you have struggled while organizing your Jupyter notebook, for making it clean, readable, and presentable, here are five notebook extensions that will make your life easier. Jupyter Notebooks Extensions are nothing but add-ons to your regular notebook functionalities. Here is a list of my five most-frequently-used notebook extensions that…