Author Archives: Pavan Kandru
Barlow twins is a novel architecture inspired by the redundancy reduction principle in the work of neuroscientist H. Barlow.
The post A Guide to Barlow Twins: Self-Supervised Learning via Redundancy Reduction appeared first on Analytics India Magazine.
Topology is the study of shapes and their properties. Topology doesn't care if you twist, bend, shear etc. the geometric objects. It simply deals with these shapes’ properties, such as the number of loops in them, no components, etc.
The post Guide to Giotto-TDA: A high-performance topological machine learning toolbox appeared first on Analytics India Magazine.
Haystack is a python framework for developing End to End question answering systems. It provides a flexible way to use the latest NLP models to solve several QA tasks in real-world settings with huge data collections.
The post What is Haystack for Neural Question Answering appeared first on Analytics India Magazine.
PaddleSeg is an Image segmentation framework based on Baidu’s PaddlePaddle(Parallel Distributed Deep Learning). It provides high performance and efficiency, SOTA segmentation models optimized for MultiNode and MultiGPU production systems.
The post Guide To Asymmetric Non-local Neural Networks Using PaddleSeg appeared first on Analytics India Magazine.
Process Mining is the amalgamation of computational intelligence, data mining and process management. It refers to the data-oriented analysis techniques used to draw insights into organizational processes.
The post Guide to PM4Py: Python Framework for Process Mining Algorithms appeared first on Analytics India Magazine.
Perceiver is a transformer-based model that uses both cross attention and self-attention layers to generate representations of multimodal data. A latent array is used to extract information from the input byte array using top-down or feedback processing
The post Guide to Perceiver: A Scalable Transformer-based Model appeared first on Analytics India Magazine.
Perceiver is a transformer-based model that uses both cross attention and self-attention layers to generate representations of multimodal data. A latent array is used to extract information from the input byte array using top-down or feedback processing
The post Guide to Perceiver: A Scalable Transformer-based Model appeared first on Analytics India Magazine.
THiNC is a lightweight DL framework that makes model composition facile. It’s various enticing advantages like Shape inference, concise model representation, effortless debugging and awesome config system, makes this a recommendable choice of framework.
The post Guide To THiNC: A Refreshing Functional Take On Deep Learning appeared first on Analytics India Magazine.
THiNC is a lightweight DL framework that makes model composition facile. It’s various enticing advantages like Shape inference, concise model representation, effortless debugging and awesome config system, makes this a recommendable choice of framework.
The post Guide To THiNC: A Refreshing Functional Take On Deep Learning appeared first on Analytics India Magazine.
THiNC is a lightweight DL framework that makes model composition facile. It’s various enticing advantages like Shape inference, concise model representation, effortless debugging and awesome config system, makes this a recommendable choice of framework.
The post Guide To THiNC: A Refreshing Functional Take On Deep Learning appeared first on Analytics India Magazine.