Search Results for "bioinformatics with python cookbook"

Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We...

Reusable code patterns which you can use as reference or copy to your project. Achieve small or large tasks using recipes that contain steps, scripts, and config files.

... feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling and practical methods, and investigates topics such as natural language processing, Applications in speech recognition, computer vision, online recommender systems, bioinformatics, and video games. Finally, the Deep Learning book provides research directions covering theoretical topics including linear factor models, autoencoders, representation learning, structured probabilistic models, etc.

This project has been moved to GitHub: https://github.com/tomschr/dbcookbook/ The DoCookBook project aims to create an open source book about DocBook and the DocBook XSL stylesheets written as a cookbook and released under a Creative Commons license.

The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE.

The dispatcher provides loosely-coupled message passing between Python objects (signal senders and receivers). It began as one of the highest-rated recipes on the Python Cookbook website