docs
tensorflow
| docs | tensorflow | |
|---|---|---|
| 3 | 223 | |
| 6,033 | 182,575 | |
| 0.5% | 0.5% | |
| 9.0 | 10.0 | |
| 8 days ago | 1 day ago | |
| Jupyter Notebook | C++ | |
| Apache License 2.0 | Apache License 2.0 |
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docs
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Anyone willing to help me out on a discord call or something?
This is the model I’m trying to understand and create my own version of: https://github.com/tensorflow/docs/blob/master/site/en/r1/tutorials/sequences/recurrent_quickdraw.md
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Well technically, C++ *is* Danish...
Seems like a fun task. Tensorflow already has a nice tutorial for image segmentation . You’d have to replace the pets by fruits and then you’d be good.
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Get started with TensorFlow and Deep Learning
TensorFlow docs here
tensorflow
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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")
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Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
What are some alternatives?
Artificial-Intelligence_resources-and-notebooks - This repo contains various different datasets and codes with various different algorithms. This also contains code and demonstrations to run an Artificial Intelligence Algorithm on the edge. It also contains many datasets where one can practice AI.
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）
rpi-urban-mobility-tracker - The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tensorflow-deep-learning - All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
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
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]
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.
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
scikit-learn - scikit-learn: machine learning in Python
introtodeeplearning - Lab Materials for MIT 6.S191: Introduction to Deep Learning
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.