MLP Classifier
tensorflow
| MLP Classifier | tensorflow | |
|---|---|---|
| - | 230 | |
| 226 | 185,904 | |
| - | 0.5% | |
| 0.0 | 10.0 | |
| over 7 years ago | 5 days ago | |
| Python | C++ | |
| MIT License | Apache License 2.0 |
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.
MLP Classifier
We haven't tracked posts mentioning MLP Classifier yet.
Tracking mentions began in Dec 2020.
tensorflow
- Create ML models that can run in any environment
-
Las 10 Mejores Herramientas de Inteligencia Artificial de Código Abierto
(https://dev-to-uploads.s3.amazonaws.com/uploads/articles/adae9icuiza0lhd532pc.png)
- TensorFlow: Democratizing Machine Learning with Open Source Power
- Release TensorFlow 2.17.0 · TensorFlow/TensorFlow
-
Top 17 Fast-Growing Github Repo of 2024
TensorFlow
-
Awesome List
GitHub Repository - The main TensorFlow repository.
-
Rebuilding TensorFlow 2.8.4 on Ubuntu 22.04 to patch vulnerabilities
The official 2.8.4 container was published in Nov 2022. That's 1.5 years of OS updates at least. I looked up the 2.8.4 source and found that it's using Ubuntu 20.04 as the base OS. Of note, we're using the x86_64 architecture according to the container image layer: ENV NVARCH=x86_64.
-
Side Quest Devblog #1: These Fakes are getting Deep
# L2-normalize the encoding tensors image_encoding = tf.math.l2_normalize(image_encoding, axis=1) audio_encoding = tf.math.l2_normalize(audio_encoding, axis=1) # Find euclidean distance between image_encoding and audio_encoding # Essentially trying to detect if the face is saying the audio # Will return nan without the 1e-12 offset due to https://github.com/tensorflow/tensorflow/issues/12071 d = tf.norm((image_encoding - audio_encoding) + 1e-12, ord='euclidean', axis=1, keepdims=True) discriminator = keras.Model(inputs=[image_input, audio_input], outputs=[d], name="discriminator")
-
Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
What are some alternatives?
Keras - Deep Learning for humans
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
HotBits Python API - Python API for HotBits random data generator
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
scikit-learn - scikit-learn: machine learning in Python
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
skflow - Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.