Python tutorials

How to create your own Question and Answering API(Flask+Docker +BERT) using haystack framework

Introduction Note from the author: In this article, we will learn how to create your own Question and Answering(QA) API using python, flask, and haystack framework with docker. The haystack framework will provide the complete QA features which are highly scalable and customizable. In this article Medium Rules, the text will be used as the target document and fine-tuning the model as well. Basic Knowledge Required: Elasticsearch & Docker This article contains the working code which can be directly build […]

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Seaborn Box Plot – Tutorial and Examples

Introduction Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. It offers a simple, intuitive, yet highly customizable API for data visualization. In this tutorial, we’ll take a look at how to plot a Box Plot in Seaborn. Box plots are used to visualize summary statistics of a dataset, displaying attributes of the distribution like the data’s range and distribution. Import Data We’ll need to select a dataset with continuous features […]

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Integrating MongoDB with Flask Using Flask-PyMongo

Introduction Building a web app almost always means dealing with data from a database. There are various databases to choose from, depending on your preference. In this article, we shall be taking a look at how to integrate one of the most popular NoSQL databases – MongoDB – with the Flask micro-framework. They are several Flask extensions for integrating MongoDB, here we’ll be using the Flask-PyMongo extension. We will also be working on a simple Todo-List API to explore the […]

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Matplotlib Box Plot – Tutorial and Examples

Introduction There are many data visualization libraries in Python, yet Matplotlib is the most popular library out of all of them. Matplotlib’s popularity is due to its reliability and utility – it’s able to create both simple and complex plots with little code. You can also customize the plots in a variety of ways. In this tutorial, we’ll cover how to plot Box Plots in Matplotlib. Box plots are used to visualize summary statistics of a dataset, displaying attributes of […]

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How to Iterate Over a Dictionary in Python

Introduction Dictionaries are one of the most used data structures in all of software development, and for a good reason. They allow us to store our data in neat key, value pairs, which in turn gives us the ability to, on average, access our data in O(1) time. While using a dictionary it’s important to know how to iterate over it. Not being able to recover the data you stored makes it practically useless. In this article, we’ll see how […]

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Python: Catch Multiple Exceptions in One Line

Introduction In this article we’re going to be taking a look at the try/except clause, and specifically how you can catch multiple exceptions in a single line, as well as how to use the suppress() method. Both of these techniques will help you in writing more accessible and versatile code that adheres to DRY (don’t repeat yourself) principles. Let’s start by looking at the problem: try: do_the_thing() except TypeError as e: do_the_other_thing() except KeyError as e: do_the_other_thing() except IndexError as […]

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Streamlit Web API for NLP: Tweet Sentiment Analysis

This article was published as a part of the Data Science Blogathon. Introduction Developing Web Apps for data models has always been a hectic task for non-web developers. For developing Web API we need to make the front end as well as back end platform. That is not an easy task. But then python comes to the rescue with its very fascinating frameworks like Streamlit, Flassger, FastAPI. These frameworks help us to build web APIs very elegantly, without worrying about […]

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Implementation of Attention Mechanism for Caption Generation on Transformers using TensorFlow

Overview Learning about the state of the art model that is Transformers. Understand how we can implement Transformers on the already seen image captioning problem using Tensorflow Comparing the results of Transformers vs attention models.   Introduction We have seen that Attention mechanisms (in the previous article) have become an integral part of compelling sequence modeling and transduction models in various tasks (such as image captioning), allowing modeling of dependencies without regard to their distance in the input or output […]

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How to Randomly Select Elements From a List in Python

Introduction Selecting a random element or value from a list is a common task – be it for randomized result from a list of recommendations or just a random prompt. In this article, we’ll take a look at how to randomly select elements from a list in Python. We’ll cover the retrieval of both singular random elements, as well as retrieving multiple elements – with and without repetition. Selecting a Random Element From Python List The most intuitive and natural […]

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Introduction to Data Visualization in Python with Pandas

Introduction People can rarely look at a raw data and immediately deduce a data-oriented observation like: People in stores tend to buy diapers and beer in conjunction! Or even if you as a data scientist can indeed sight read raw data, your investor or boss most likely can’t. In order for us to properly analyze our data, we need to represent it in a tangible, comprehensive way. Which is exactly why we use data visualization! The pandas library offers a […]

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