Finally GSoC’21 community bonding period is over and now we’ll be moving to the coding phase. It was an amazing journey for me. I made some contributions to the projects and learned a lot of things from my mentors. In this blog, I’ll be sharing my journey with Hydra Ecosystem as an open-source contributor.

I started my journey of open-source contributions with Hydra Ecosystem. Hydra Ecosystem aims to build a set of tools to automate the process of building REST APIs and Next-Gen smart clients which follow the principle of Semantic Web, Linked Data, and JSON-LD. Hydra is a vocabulary…

This is the first piece from my upcoming series of advance Django included with Test-driven development. [ Upcoming — FastAPI ]

The Django Signals can be used to get notified when certain events occur. They can also be used for database logging. Let’s say you want to perform some logic every time a given model instance is updated, but there are several places in your codebase that this model can be updated. You can do that using signals, hooking some pieces of code to be executed every time this specific model’s save method is triggered.

In this piece, we’ll look…

The U-Net architecture is built using the Fully Convolutional Network and designed in a way that it gives better segmentation results in medical imaging. It was first designed by Olaf Ronneberger, Philipp Fischer, and Thomas Brox in 2015 to process biomedical images []. Convolutional neural networks are generally used for image classification problems, but in biomedical cases, we have to localize the area of abnormality as well.

It has a “U” shape. U-Net architecture is symmetric and it’s functioning is somewhat similar to auto-encoders. It can be narrowed down into three major parts — The contracting(downsampling) path, Bottleneck, and expanding(upsampling)…

Natural Language Processing or NLP is a field of Artificial Intelligence and Deep Learning that gives the machines the ability to read, understand, and derive meaning from human languages and focuses on the interaction between data science and human language.

This attempt is a sneak peek and primarily focuses on performing a basic Sentiment Analysis using Tensorflow and Keras. A commonly used approach would be using a Convolutional Neural Network (CNN) to do sentiment analysis. Keras, however, has Embedding() Layers, GlobalAveragePooling1D() and LSTM layers which can be used to build a much accurate machine learning model.

Keras’s Sequential API is…

Hasan Faraz Khan

An undergraduate Computer Science student and Pythonista . Pursuing my BSc. (Hons) from Aligarh Muslim University, India. Contributing to Open-Source softwares.

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