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Articles by Subhradeep Rang
A Step-by-Step Guide to PDF Chatbots with Langchain and Ollama
In an era where technology continues to transform the way we interact with information, the concept of a PDF chatbot brings a new level of convenience and efficiency to the table. This article delves into the intriguing realm of creating a PDF chatbot using Langchain and Ollama, where open-source models become accessible with minimal configuration.
A Beginner’s Guide to Context Manager
This article was published as a part of the Data Science Blogathon. Introduction When we watch youtube videos or any tutorial about data analysis, we see that the context mainly used in reading or writing some texts from a file so that we don’t have to write the code for closing the file whenever our task is finished. But this is not the only use-case of this context manager. We can use context managers in more relaxed ways.
An Introduction to Julia for Data Analysis
This article was published as a part of the Data Science Blogathon. Which language do we use when it comes to data analysis? Of course, Python, isn’t it? But there is one more language for data analysis which is growing rapidly. Some of you might guess the language – I am talking about Julia. I always like to learn something new. So when it comes to data analysis, of course, I will give it a try. After learning this language, I was pretty impressed.
Analysis of Restaurants in the United States
This article was published as a part of the Data Science Blogathon. Introduction After working for a long time in the office, suddenly, we felt a storm brewing in our stomach, saying Hey! I need food. Then you just come out on the road and start searching for a nearby restaurant – it can be part of a chained restaurant or an independent restaurant. Search for nearby restaurants makes restaurant owners think about opening multiple outlets to grow their business.
Analysis of Australian Shark Attacks
Beginner Data Visualization Machine Learning Python This article was published as a part of the Data Science Blogathon. Introduction Recently I searched for an interesting dataset to learn something new. After searching for a long time, I got a dataset on Shark Attacks in Australia. This dataset contains about 1,100 + shark bites and attempted shark bites between 1791 and early 2022, gathered by the Taronga Conservative Society.
Making a Multipaged Application using Streamlit
This article was published as a part of the Data Science Blogathon. Introduction In this article, I will discuss everything about Streamlit Multipage functionality, how to use it, and its pros and cons. You are going to learn so many things from this article. So, just take a cup of tea and read on. Project Structure in Streamlit To make a multipage app in Streamlit, you must maintain a project structure.
Analysis on Dark Chocolates using Python and Plotly
Subhradeep Rang — Published On July 26, 2022 and Last Modified On July 26th, 2022 Beginner Data Visualization Libraries This article was published as a part of the Data Science Blogathon. Introduction Who doesn’t love chocolate? Everybody does. But not everyone likes dark chocolates as they taste bitter. But if you want to be healthy and want to overcome some stressful situation, this bad guy will give you some relief. Just take a bite of it.
A Comprehensive Guide to Heroku Postgres
This article was published as a part of the Data Science Blogathon. Introduction Recently I was doing an analysis, and in this analysis, I wanted to take the data from a remote database. I previously used Azure, but I had to delete the database after learning. Otherwise, they will deduct money from your Azure balance. This is not a good experience for students. So I am searching for a free database in which I don’t have to worry about the money. Then I came to know about Heroku Postgres.
Video Game Clustering Using Python
This article was published as a part of the Data Science Blogathon. Intr In this article, I am goinoject while learning about the K-Means Clustering. After reading this article, you can able to: Impute missing values using KNN. Reduce the dimensionality of data. Apply K-Means for clustering. I am writing this article in such a way that anyone can understand what I am doing. So, take a cup of coffee and read on. Import Necessary Packages Let’s import the necessary packages. The packages are given below.
Customer Churn Prediction of a Telecom Company Using Python
This article was published as a part of the Data Science Blogathon. Introduction to Customer Churn Prediction After taking some courses on Data Science, I feel a necessity for applying those skills to some projects. For this, I analyzed and made a machine learning model on a dataset that comes from an Iranian telecom company, with each row representing a customer over a year period. I took this dataset from Kaggle. In this article, I am going to share my experience while working with this data.
Scraping Jobs on LinkedIn Using Scrapy
This article was published as a part of the Data Science Blogathon. Introduction Recently I have been working on a personal project in which I want to extract the skills from the resume and match thos I chose Linkedin for scraping jobs, and their descriptions as this site are the most used for searching jobs. I also need a domain-speso collecting data from others will not work for me. Before starting this article, I want to inform you that this article is not for absolute beginners.
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