Text Featurization In Machine Learning — In Machine Learning, it is nice when models are simple and interpretable, since it reduces the burden of debugging a complex model when things don’t work. But simple models do not always lead to the best results. Similarly, there are simple text featurizer which doesn’t result in effective models. For…

Branching A branch represents an independent line of development. Branches serve as an abstraction for the edit/stage/commit process. We can think of them as a way to request a brand new working directory, staging area, and project history. All the new commits are recorded in the history of the current branch…

Git Git is a free and open-source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. Git is easy to learn and has a tiny footprint with lightning-fast performance. …

Open source software (OSS) is released under a license where the author grants users permission to use, modify, build features of, and distribute the software to anyone and anywhere. The license dictates how the software can be used, modified, and distributed. There are different licenses under the open source initiative…

Self-Supervised Approach To Learning — What is Self-Supervised Learning? It is a method of machine learning where the model learns from the supervisory signal of the data unlike supervised learning where separate labels are specified for each observation. It is also known as Representation Learning. Note, the model’s learned representation is used for downstream tasks like BERT, where language…

What is Self-Supervised Learning? It is a method of machine learning where the model learns from the supervisory signal of the data unlike supervised learning where separate labels are specified for each observation. It is also known as Representation Learning. Note, the model’s learned representation is used for…

Recently, I’ve completed 30 Days of ML with Pytorch , where I explored all the major machine learning algorithms and basics of deep learning with concepts like activation, optimizer, loss functions etc. However, the idea behind starting 30 Days of ML with PyTorch is to learn the implementation of machine…

Learning with no guidance — In previous blog post on supervised learning, we have seen that each observed data has a label attached to it, making it easy to train a model. However, in unsupervised learning, the algorithm finds the hidden patterns in unlabeled data. A popular technique in unsupervised learning is Clustering Algorithms.

An attempt to understand transformers — Transformers architecture was introduced in Attention is all you need paper. Similar to CNN for Computer vision, the transformers are for NLP. A simple daily use case one can build using transformers is Conversational Chatbot.