Top 10 Python Mxnet Projects
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.Project mention: The Transformer in Machine Translation | reddit.com/r/MindSporeOSS | 2022-01-13
GitHub's article on Dive into Deep Learning
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.Project mention: [D] PyTorch Distributed Training Libraries: What are the current options? | reddit.com/r/MachineLearning | 2021-12-07
Check out Horovod - https://github.com/horovod/horovod
Deliver Cleaner and Safer Code - Right in Your IDE of Choice!. SonarLint is a free and open source IDE extension that identifies and catches bugs and vulnerabilities as you code, directly in the IDE. Install from your favorite IDE marketplace today.
State-of-the-art 2D and 3D Face Analysis ProjectProject mention: What would be the best performing face recognition model/architecture? | reddit.com/r/deeplearning | 2021-12-31
Original repo : https://github.com/deepinsight/insightface
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.Project mention: [R] Importing TensorFlow neural networks stored as *.h5 | reddit.com/r/MachineLearning | 2021-12-06
The only way I found online is to convert the *.h5 files to MXNet files using Microsoft model management of deep neural networks (link)
AutoGluon: AutoML for Text, Image, and Tabular DataProject mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
Machine Learning Management & Orchestration Platform (Monorepo for Polyaxon's MLOps Tools)Project mention: [D] Productionalizing machine learning pipelines for small teams | reddit.com/r/MachineLearning | 2021-08-08
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
🔮 A refreshing functional take on deep learning, compatible with your favorite librariesProject mention: good examples of functional-like python code that one can study? | reddit.com/r/functionalprogramming | 2021-06-29
thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable
OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.
AI Face Recognition/Person Detection NVR. Machine Learning On The Edge, turn your Camera into AI-powered with Jetson Nano and telegram to protect your privacy.Project mention: Private Home Security and AI | reddit.com/r/privacytoolsIO | 2021-01-30
Shinobi + DeepCamera?
Transfer Learning library for Deep Neural Networks.Project mention: [R] Fast Adaptation with Linearized Neural Networks | reddit.com/r/MachineLearning | 2021-03-31
Abstract: The inductive biases of trained neural networks are difficult to understand and, consequently, to adapt to new settings. We study the inductive biases of linearizations of neural networks, which we show to be surprisingly good summaries of the full network functions. Inspired by this finding, we propose a technique for embedding these inductive biases into Gaussian processes through a kernel designed from the Jacobian of the network. In this setting, domain adaptation takes the form of interpretable posterior inference, with accompanying uncertainty estimation. This inference is analytic and free of local optima issues found in standard techniques such as fine-tuning neural network weights to a new task. We develop significant computational speed-ups based on matrix multiplies, including a novel implementation for scalable Fisher vector products. Our experiments on both image classification and regression demonstrate the promise and convenience of this framework for transfer learning, compared to neural network fine-tuning. Code is available at this https URL.
Functions and classes for gradient-based robot motion planning, written in Ivy. (by unifyai)Project mention: First 2022 newsletter 🚀 Many upcoming events | reddit.com/r/2D3DAI | 2022-01-22
(February 28) - Unifying all Machine Learning Frameworks. This is a hands-on interactive coding session and live demo. We will explain how Ivy is solving an ML unification problem.
Python Mxnet related posts
First 2022 newsletter 🚀 Many upcoming events
1 project | reddit.com/r/2D3DAI | 22 Jan 2022
What would be the best performing face recognition model/architecture?
3 projects | reddit.com/r/deeplearning | 31 Dec 2021
Why do most facial recognition algorithms use a hypersphere manifold?
3 projects | reddit.com/r/deeplearning | 5 Dec 2021
Finding similarity between two faces using Siamese Network/Oneshot learning
1 project | reddit.com/r/learnmachinelearning | 3 Nov 2021
Can Someone please guide me on this project?
1 project | reddit.com/r/computervision | 23 May 2021
just released my Clojure AI book
4 projects | reddit.com/r/Clojure | 23 May 2021
[R] Fast Adaptation with Linearized Neural Networks
1 project | reddit.com/r/MachineLearning | 31 Mar 2021
What are some of the best open-source Mxnet projects in Python? This list will help you:
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