Alternatives and similar repositories for MidcurveNN

Users that are interested in MidcurveNN are comparing it to the libraries listed below

• abheesht17 / whisper-keras
  ☆16Updated 2 years ago
• sayakpaul / deploy-hf-tf-vision-models
  This repository shows various ways of deploying a vision model (TensorFlow) from 🤗 Transformers.
  ☆30Updated 3 years ago
• amaarora / melanoma_wandb
  ☆15Updated 3 years ago
• sayakpaul / PAWS-TF
  Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
  ☆45Updated 4 years ago
• soumik12345 / nerf.jax
  A minimal TPU compatible Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.
  ☆13Updated 3 years ago
• sayakpaul / dreambooth-keras
  Implementation of DreamBooth in KerasCV and TensorFlow.
  ☆88Updated 2 years ago
• dnth / timm-flutter-pytorch-lite-blogpost
  PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter.
  ☆45Updated 2 years ago
• shahrukhx01 / adversarial-ml-101
  A beginner friendly repository for getting started with adversarial machine learning in PyTorch
  ☆26Updated 3 years ago
• sayakpaul / Distributed-Training-in-TensorFlow-2-with-AI-Platform
  Contains code to demonstrate distributed training in TensorFlow 2 with AI Platform and custom Docker contains.
  ☆20Updated 4 years ago
• deep-diver / semantic-segmentation-ml-pipeline
  Machine Learning Pipeline for Semantic Segmentation with TensorFlow Extended (TFX) and various GCP products
  ☆95Updated 2 years ago
• multi-modal-ai / production-hub
  Hands-on hub to learn techniques to optimize and serve AI models to production the most optimal way.
  ☆13Updated 2 months ago
• ariG23498 / timm-wrapper-examples
  Notebooks to demonstrate TimmWrapper
  ☆16Updated 10 months ago
• anyscale / e2e-llm-workflows
  Fine-tune an LLM to perform batch inference and online serving.
  ☆113Updated 5 months ago
• roboflow / deploy-models-with-grpc-pytorch-asyncio
  Article about deploying machine learning models using grpc, pytorch and asyncio
  ☆30Updated 3 years ago
• capjamesg / sam-clip
  Use Grounding DINO, Segment Anything, and CLIP to label objects in images.
  ☆33Updated last year
• philschmid / amazon-sagemaker-gpt-j-sample
  ☆29Updated 2 years ago
• explodinggradients / notes
  Research notes and extra resources for all the work at explodinggradients.com
  ☆24Updated 8 months ago
• msaroufim / sixfigurecareer
  Pip install yourself to a six figure career!
  ☆12Updated 4 years ago
• The-AI-Summer / learn-deep-learning
  AI Summer's complete catalog of articles
  ☆112Updated 3 years ago
• angary / simulated-annealing-tsp
  Parameterising Simulated Annealing for the Travelling Salesman Problem
  ☆59Updated 3 months ago
• suvoooo / Learn-TensorFlow
  Learning Tensorflow Step by Step:: Concepts, Examples & Applications
  ☆56Updated 5 months ago
• muellerzr / nbdistributed
  Seemless interface of using PyTOrch distributed with Jupyter notebooks
  ☆53Updated 2 months ago
• sayakpaul / Spatial-Transformer-Networks-with-Keras
  This repository provides a Colab Notebook that shows how to use Spatial Transformer Networks inside CNNs in Keras.
  ☆37Updated 3 years ago
• Pavankunchala / Work-Showcase
  Deep Learning and Computer Vision Applications using Streamlit
  ☆78Updated 3 years ago
• ishandutta0098 / zero-to-lightning
  zero-to-lightning
  ☆31Updated last year
• sayakpaul / BiT-jax2tf
  This repository hosts the code to port NumPy model weights of BiT-ResNets to TensorFlow SavedModel format.
  ☆14Updated 3 years ago
• SkalskiP / sketchy-vision
  Each week I create sketches covering key Computer Vision concepts. If you want to learn more about CV stick around!
  ☆149Updated 2 years ago
• sayakpaul / GCP-ML-API-Demos
  Contains Colab Notebooks show cool use-cases of different GCP ML APIs.
  ☆10Updated 5 years ago
• JINO-ROHIT / fastapi_with_celery_redis
  serving a torch model using Celery, Redis and RabbitMQ to serve users asynchronously
  ☆25Updated last year
• soumik12345 / Radium
  Radium is a Ray Tracing Engine written in C++ that runs on the CPU using shared-memory multiprocessing
  ☆20Updated 4 years ago