bidd-molmap
TensorFlow-Examples
| bidd-molmap | TensorFlow-Examples | |
|---|---|---|
| 1 | 2 | |
| 134 | 43,236 | |
| - | - | |
| 4.2 | 0.0 | |
| about 1 month ago | 3 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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bidd-molmap
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Researchers From Tsinghua University, The National University of Singapore Have Recently Developed An AI Tool Called ‘MolMapNet’ That Predicts Drugs Pharmaceutical Properties
Github: https://github.com/shenwanxiang/bidd-molmap
TensorFlow-Examples
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Keras vs. TensorFlow
A linear regression model
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Tensorman and RTX 30-Series GPU's
When I run this simple project, the log output is below. There is a 5-minute pause at 16:48. There is a second pause at the end of the script before the output of the example (final output excluded). This project runs quickly if I exclude "--gpu" and run it on the CPU.
What are some alternatives?
deepchem - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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deep-learning-drizzle - Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
graphkit-learn - A python package for graph kernels, graph edit distances, and graph pre-image problem.
DrugDiscovery-Tox21 - Drug discovery project by making use of the Tox-21 dataset.
pyVHR - Python framework for Virtual Heart Rate
TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos
Deep-Learning-Hardware-Benchmark - This repository contains the proposed implementation for benchmarking in order to evaluate whether a setup of hardware is feasible for deep learning projects.
rmi - A learned index structure
Deep-Learning-With-TensorFlow-Blog-series - All the resources and hands-on exercises for you to get started with Deep Learning in TensorFlow [Moved to: https://github.com/Rishit-dagli/Deep-Learning-With-TensorFlow]
TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!
models - A collection of pre-trained, state-of-the-art models in the ONNX format