DeepSpeed Vs Horovod: A Comparative Analysis
A comparative analysis of open-source deep learning optimization libraries DeepSpeed and Horovod for advancing large-scale model training.
Best Python Libraries For Data Science In 2021
Python is an interpreted, interactive, portable and object-oriented programming language. This open-sourced general-purpose language runs on many Unix variants, including Linux and macOS, and Windows. Python has applications in hacking, computer vision, data visualisation, 3D Machine Learning, robotics, and is a favourite of developers worldwide. Below, we list the ten most popularly used Python libraries […]
Beginners Guide To Text Generation With RNNs
Text Generation is a task in Natural Language Processing in which text is generated with some constraints such as initial characters words
Getting Started With Sentiment Analysis Using TensorFlow Keras
Sentiment Analysis is a text classification application in which a given text is classified into either a positive class or a negative class
Getting Started With Image Generation Using TensorFlow Keras
Image Generation is one of the most curious applications in Computer Vision. Variational Autoencoders and GANs are the preferred base models
Getting Started With Semantic Segmentation Using TensorFlow Keras
Semantic segmentation in computer vision is the supervised process of pixel-level image classification into two or more Object classes
Exploring Transfer Learning Using TensorFlow Keras
Transfer Learning is the approach of making use of an already trained deep learning model along with its weights for a related task
Getting Started With Computer Vision Using TensorFlow Keras
Computer Vision attempts what a human brain does with the aid of eyes. It is a branch of Deep Learning that deals with images and videos.
Getting Started With Deep Learning Using TensorFlow Keras
Deep Learning is a subset of Machine learning. It was developed to have an architecture and functionality similar to that of a human brain.
Guide to TensorFlow Extended(TFX): End-to-End Platform for Deploying Production ML Pipelines
Ever since Google has publicised Tensorflow, its application in Deep Learning has been increasing tremendously. It is used even more in research and production for authoring ML algorithms. Though it is flexible, it does not provide an end-to-end production system. On the other hand, Sibyl has end-to-end facilities but lacks flexibility. Google then came up […]
Introduction To Keras Graph Convolutional Neural Network(KGCNN) & Ragged Tensor
KGCNN offers a straightforward and flexible integration of graph operations into the Tensorflow-Keras framework using RaggedTensors.
Reinventing Deep Learning Operation Via Einops
Einops, an abbreviation of Einstein-Inspired Notation for operations is an open-source python framework for writing deep learning code in a new and better way. Einops provides us with new notation & new operations. It is a flexible and powerful tool to ensure code readability and reliability with minimalist yet powerful API. Supported Frameworks numpy pytorch […]
