Detailed Step by Step Process of a Sentiment Analysis in Python — With the massive introduction of ChatGPT and other similar types of applications, it’s impossible not to notice the importance or implications of Natural Language Processing in the industry today. Also, from social media and online businesses, a huge amount of text data is generated every day. Businesses are also working…

Some Commonly Used Text Preprocessing Techniques in Python With Examples — In this age of social media and online business era, text data are coming from everywhere. However, dealing with text data is tricky. Because raw text may come in with all types of impurities, unnecessary noises, spelling mistakes, and more. So, it is necessary to go through proper preprocessing before…

How to calculate Tfidf values manually and using sklearn — TFIDF is a method to convert texts to numeric form for machine learning or AI models. In other words, TFIDF is a method to extract features from texts. This is a more sophisticated method than the CountVectorizer() method I discussed in my last article. The TFIDF method provides a score…

Everything you need to know to use CountVectorizer efficiently in Sklearn — The most basic data processing that any Natural Language Processing (NLP) project requires is to convert the text data to the numeric data. As long as the data is in text form we cannot do any kind of computation action on it. There are multiple methods available for this text-to-numeric…

Use of GradientTape to Update the Weights — TensorFlow is arguably the most popular library for deep learning. I wrote so many tutorials on TensorFlow before and still continuing. TensorFlow is very well organized and easy to use package where you do not need to worry about model development and model training too much. Pretty much most of…

Data Cleaning, Analysis, Visualization, Feature Selection, Predictive Modeling — I have a few tutorials on Exploratory Data Analysis before. But I feel I should do some more of that. Taking a dataset and explore it, doing the data cleaning, analytics, visualization, and prediction model all in one piece is necessary. As a Data Scientist or Data Analyst, we may…

A cutting-edge unsupervised method for noise removal, dimensionality reduction, anomaly detection, and more — All the tutorials about TensorFlow and neural networks I have shared until now have been about supervised learning. This one will be about the Autoenocder which is an unsupervised learning technique. If I want to express it simply, autoencoders reduce the noises from the data by compressing the input data…

Learn the techniques behind object detection (and much more) with example code. — Neural Networks are great and very popular in AI/ML spaces, but they require too much data to train. For tasks like object detection, signature verification, voice verification, and prescription pills recognition regular neural network techniques would be much more time-consuming and expensive because of this excessive data requirement. In these…

Detail Explanation of Code For Beginners I wrote a tutorial on some common transform functions in Apache Beam in a previous tutorial that covered map, filter, and combinePerKey(). This tutorial will be for ParDo transform which is nothing but another way of doing Map. But the difference is ParDo applies…