get-started-with-JAX
uvadlc_notebooks
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0.0 | 6.6 | |
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Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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get-started-with-JAX
- How to stay up-to-date with the latest AI company announcements and events?
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Tips to become self taught machine learning engineer
The AI Epiphany
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Machine Learning with JAX - From Hero to HeroPro+ | Tutorial #2
Code: https://github.com/gordicaleksa/get-started-with-JAX
uvadlc_notebooks
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I miss the old days where people asked me to recreate “Facebook” or “Twitter”
So, I don’t have anything simple that’s readily available, and I don’t know how much you’d get from the code itself without some background. But I would recommend the UVA Deep Learning tutorials. Particularly, I’d recommend trying the autoencoder as a good start (tutorial 9). Autoencoders are very easy and fast models to train.
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[D] Favorite Colab Notebooks / runnable tutorials on adversarial CV
DL course from the University of Amsterdam:Github and Colab including another FGSM example
What are some alternatives?
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
tensor-sensor - The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
hyper-nn - Easy Hypernetworks in Pytorch and Jax
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.
TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!
JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
jaxrl - JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
labml - 🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱