Hey guys! this blog is about a mini project of scraping the contents from the websites. I hope you enjoy this article. We are using Beautiful soup to scrape the text data. Beautiful Soup is a Python package for parsing HTML and XML documents. It creates a parse tree for parsed pages that can be used to extract data from HTML, which is useful for web scraping.

Python is one of the leading programming languages across the globe. It is used in many contexts from data science, robotics, web development to gaming, and rapid prototyping. Its simple syntax makes Python programs really easy to read and write, ensuring a rapid learning curve. Additionally, Python has'batteries included' -- multiple libraries (standard and third-party) that will greatly facilitate your work as a programmer. Although a basic programming level can be reached faster than with other programming languages, it definitely takes some time to master Python.

Web Scraping is the process of collecting data from the internet by using various tools and frameworks. Sometimes, It is used for online price change monitoring, price comparison, and seeing how well the competitors are doing by extracting data from their websites. Web Scraping is as old as the internet is, In 1989 World wide web was launched and after four years World Wide Web Wanderer: The first web robot was created at MIT by Matthew Gray, the purpose of this crawler is to measure the size of the worldwide web. Beautiful Soup is a Python library that is used for web scraping purposes to pull the data out of HTML and XML files. It creates a parse tree from page source code that can be used to extract data in a hierarchical and more readable manner.

In 2017, a friend gave me some sourdough starter to make bread with, and ever since then, my life has changed. It sounds cheesy, but I discovered a hobby that has led me to buy almost 200 pounds of flour at a time (seriously), develop a biweekly pizza baking habit, and dream of what bread I'm going to make in the coming days! Because I spend a lot of time baking sourdough and experimenting with new formulas, I wanted to see if I could create an artificial intelligence-powered recipe generator that would predict something for me to make! One of my go-to websites for technique, tips and tricks has been the helpful bread baking forum, The Fresh Loaf, where people ask questions and post recipes. My idea was to scrape this website and get data to train a neural network to generate new bread recipes -- and that's what I did.

I recently joined Jatana.ai as NLP Researcher (Intern) and I was asked to work on the text classification use cases using Deep learning models. In this article I will share my experiences and learnings while experimenting with various neural networks architectures. Text classification was performed on datasets having Danish, Italian, German, English and Turkish languages. One of the widely used Natural Language Processing & Supervised Machine Learning (ML) task in different business problems is "Text Classification", it's an example of Supervised Machine Learning task since a labelled dataset containing text documents and their labels is used for training a classifier. The goal of text classification is to automatically classify the text documents into one or more predefined categories. Text Classification is a very active research area both in academia and industry.