Author Archives: Nikita Shiledarbaxi - Page 5
Streamlit.io is an open-source project which provides an interactive framework for Data Science experimentations. We have already covered real-time object detection and building a COVID-19 dashboard using the Streamlit API in our previous articles. In this article, we are going to use Streamlit for another use case called time series forecasting. Before proceeding, refer to…
The post How to deploy Time Series Forecasting models Using StreamLit appeared first on Analytics India Magazine.
Universal sentence encoder models encode textual data into high-dimensional vectors which can be used for various NLP tasks. It was introduced by Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Yun-Hsuan Sung, Brian Strope and Ray Kurzweil (researchers at Google Research) in…
The post Guide To Universal Sentence Encoder With TensorFlow appeared first on Analytics India Magazine.
Universal sentence encoder models encode textual data into high-dimensional vectors which can be used for various NLP tasks. It was introduced by Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Yun-Hsuan Sung, Brian Strope and Ray Kurzweil (researchers at Google Research) in…
The post Guide To Universal Sentence Encoder With TensorFlow appeared first on Analytics India Magazine.
Universal sentence encoder models encode textual data into high-dimensional vectors which can be used for various NLP tasks. It was introduced by Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Yun-Hsuan Sung, Brian Strope and Ray Kurzweil (researchers at Google Research) in…
The post Guide To Universal Sentence Encoder With TensorFlow appeared first on Analytics India Magazine.
learn2learn is a software library designed for meta-learning research. It was introduced by Sebastien M. R. Arnold from University of Southern California, Praateek Mahajan from Iterable Inc., Debajyoti Datta from University of Virginia, Ian Bunner from University of Waterloo and Konstantinos Saitas Zarkias from KTH Royal Institute of Technology and Research Institute of Sweden (RISE)…
The post Guide To learn2learn: A Library For Meta-Learning Research appeared first on Analytics India Magazine.
SciBERT is a pre-trained BERT-based language model for performing scientific tasks in the field of Natural Language Processing (NLP). It was introduced by Iz Beltagy, Kyle Lo and Arman Cohan – researchers at the Allen Institute for Artificial Intelligence (AllenAI) in September 2019 (research paper). Since the architecture of SciBERT is based on the BERT…
The post Guide To SciBERT: A Pre-trained BERT-Based Language Model For Scientific Text appeared first on Analytics India Magazine.
Open Federated Learning (OpenFL) is a Python 3 library designed for implementing a federated learning approach in Machine Learning experiments. The framework was developed by Intel Labs and Intel Internet of Things Group. If you are unfamiliar with the term ‘federated learning’, read ‘What is federated learning?’, ‘How does it work?’ and ‘Advantages of federated…
The post Guide to Open Federated Learning (OpenFL) – An Intel’s Python Framework appeared first on Analytics India Magazine.
Open Federated Learning (OpenFL) is a Python 3 library designed for implementing a federated learning approach in Machine Learning experiments. The framework was developed by Intel Labs and Intel Internet of Things Group. If you are unfamiliar with the term ‘federated learning’, read ‘What is federated learning?’, ‘How does it work?’ and ‘Advantages of federated…
The post Guide to Open Federated Learning (OpenFL) – An Intel’s Python Framework appeared first on Analytics India Magazine.
Model optimization plays a vital role in improving the performance of a Deep Neural Network (DNN). Techniques such as Batch Normalization and Weight Standardization perform Z-score standardization on activations or weights of the network. This article describes a novel optimization method called ‘Gradient Centralization (GC)’ which works directly on gradients instead. It was introduced by…
The post Hands-on Guide to Gradient Centralization appeared first on Analytics India Magazine.
GANSynth is a state-of-the-art method for synthesizing high-fidelity and locally coherent audio using Generative Adversarial Networks (GANs). Hence the name GANSynth (GAN used for audio Synthesis). It was introduced by Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue and Adam Roberts – researchers at the Google AI in 2019 (research paper). Autoregressive…
The post Hands-on Guide To GANSynth: An Adversarial Neural Audio Synthesis Technique appeared first on Analytics India Magazine.