Ankit Das

Ankit Das

A data analyst with expertise in statistical analysis, data visualization ready to serve the industry using various analytical platforms. I look forward to having in-depth knowledge of machine learning and data science. Outside work, you can find me as a fun-loving person with hobbies such as sports and music.
Vocabulary Builder
Developers Corner

How To Create A Vocabulary Builder For NLP Tasks?

The vocabulary helps in pre-processing of corpus text which acts as a classification and also a storage location for the processed corpus text. Once a text has been processed, any relevant metadata can be collected and stored.In this article, we will discuss the implementation of vocabulary builder in python for storing processed text data that can be used in future for NLP tasks.

Developers Corner

Optimization In Data Science Using Multiprocessing and Multithreading

In the real world, the size of datasets is huge which comes as a challenge for every data science programmer. Working on it takes a lot of time, so there is a need for a technique that can increase the algorithm’s speed. Most of us are familiar with the term parallelization that allows for the distribution of work across all available CPU cores. Python offers two built-in libraries for this process, multiprocessing and multithreading.

Deploy model
Developers Corner

Complete Guide To Model Deployment Using Flask in Google Cloud Platform

In real-world, training and model prediction is one phase of the machine learning life-cycle. But it won’t be helpful to anyone other than the developer as no one will understand it. So, we need to create a frontend graphical tool that users can see on their machine. The easiest way of doing it is by deploying the model using Flask.

In this article, we will discuss how to use flask for the development of our web applications. Further, we will deploy the model on google platform environment.

Developers Corner

Hands-On Guide To Detecting SMS Spam Using Natural Language Processing

In this era, Short message service or SMS is considered one of the most powerful means of communication. As the dependence on mobile devices has drastically increased over the period of time it has led to an increased number of attacks in the form of SMS Spam.The main aim of this article is to understand how to build an SMS spam detection model. We will build a binary classification model to detect whether a text message is spam or not.

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