TensorFlow-Tutorials
m1-machine-learning-test
| TensorFlow-Tutorials | m1-machine-learning-test | |
|---|---|---|
| 2 | 3 | |
| 9,250 | 498 | |
| - | - | |
| 0.0 | 0.0 | |
| over 3 years ago | 27 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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TensorFlow-Tutorials
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Probabilistic forecasting
"deep neural network" https://github.com/Hvass-Labs/TensorFlow-Tutorials
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Plagiarism is just bad
The majority of this code is taken from the TensorFlow-Tutorials. I highly recommend them to those who want to get started with TensorFlow.
m1-machine-learning-test
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Need help with successfully installing tensorflow on a Mac running M1 chip
Here's a pretty decent walkthrough in the readme: https://github.com/mrdbourke/m1-machine-learning-test
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TensorFlow won’t work with new M1 Mac. Please help please please please!
I got a new M1 Mac a few weeks ago and I’m having issues downloading and using tensorflow. I used this method to install it but once I get to the Jupyter Notebook test step, it says that the tensorflow file isn’t found. The tutorial that I found seemed really new so I am super confused! Could someone please help me?? I’m feeling very dumb and incompetent.
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M1 Ultra for deep learning
I found this repo which has some benchmarks for other M1s: https://github.com/mrdbourke/m1-machine-learning-test/tree/main/results
What are some alternatives?
car-damage-detection - Detectron2 for car damage detection using custom dataset
swift - Swift for TensorFlow
YOLO_Object_Detection - This is the code for "YOLO Object Detection" by Siraj Raval on Youtube
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Practical_RL - A course in reinforcement learning in the wild
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
Deep-Learning-In-Production - Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
TextWorld - TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions - Solutions of Reinforcement Learning, An Introduction
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0