pomegranate
TensorFlow-Examples
pomegranate | TensorFlow-Examples | |
---|---|---|
2 | 2 | |
3,258 | 43,210 | |
- | - | |
6.4 | 0.0 | |
about 2 months ago | 3 months ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pomegranate
- Pomegranate v1.0.0: towards merging probabilistic models with neural networks
-
Generalized sequence from a set of similar sequences?
maybe https://github.com/jmschrei/pomegranate
TensorFlow-Examples
-
Keras vs. TensorFlow
A linear regression model
-
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?
nautilus_trader - A high-performance algorithmic trading platform and event-driven backtester
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
vscode-calva-setup - My VS Code / Calva / Portal / Joyride setup
graphkit-learn - A python package for graph kernels, graph edit distances, and graph pre-image problem.
pandarallel - A simple and efficient tool to parallelize Pandas operations on all availableĀ CPUs
pyVHR - Python framework for Virtual Heart Rate
spaCy - š« Industrial-strength Natural Language Processing (NLP) in Python
TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos
madmom - Python audio and music signal processing library
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.
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
rmi - A learned index structure