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Taichi TAKAYAMA's starred repositories

pytorch-domain-adaptation

A collection of implementations of adversarial domain adaptation algorithms

Language:PythonMIT59600

hyperspectral-regression

Code examples for the book chapter "Supervised, Semi-Supervised and Unsupervised Learning for Hyperspectral Regression".

Language:Jupyter NotebookBSD-3-Clause2700

awesome-transfer-learning

Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)

169800

torchshard

Slicing a PyTorch Tensor Into Parallel Shards

Language:PythonApache-2.029300

lucas-processing

LUCAS Soil Texture Processing Scripts

Language:PythonBSD-3-Clause200

Inception-InceptionResNet-SEInception-SEInceptionResNet-1D-2D-Tensorflow-Keras

Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)

Language:Jupyter NotebookMIT3200

Multi-Scale-1D-ResNet

pytorch code of multi scale 1d resnet, we hope it will help your research

Language:PythonMIT20400

lightning-bolts

Toolbox of models, callbacks, and datasets for AI/ML researchers.

Language:PythonApache-2.0166000

Ensemble-Pytorch

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

Language:PythonBSD-3-Clause105200

optuna-examples

Examples for https://github.com/optuna/optuna

Language:PythonMIT63500

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.

Language:PythonMIT578200

deep-learning-model-convertor

The convertor/conversion of deep learning models for different deep learning frameworks/softwares.

323900

lightning-hydra-template

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Language:Python385600

-deprecated-NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV

Computer vision container that includes Jupyter notebooks with built-in code hinting, Anaconda, CUDA 11.8, TensorRT inference accelerator for Tensor cores, CuPy (GPU drop in replacement for Numpy), PyTorch, PyTorch geometric for Graph Neural Networks, TF2, Tensorboard, and OpenCV for accelerated workloads on NVIDIA Tensor cores and GPUs.

Language:Jupyter NotebookApache-2.015800

incremental_training

Repo that relates to the Medium blog 'Keeping your ML model in shape with Kafka, Airflow' and MLFlow'

Language:Python12000

kedro-mlflow

A kedro-plugin for integration of mlflow capabilities inside kedro projects (especially machine learning model versioning and packaging)

Language:PythonApache-2.019400

gpu-jupyter

GPU-Jupyter: Leverage the flexibility of Jupyterlab through the power of your NVIDIA GPU to run your code from Tensorflow and Pytorch in collaborative notebooks on the GPU.

Language:Jupyter NotebookApache-2.068300

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Language:PythonApache-2.0789500

autogluon

Fast and Accurate ML in 3 Lines of Code

Language:PythonApache-2.0742800

aesara

Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

Language:PythonNOASSERTION116600

cudf

cuDF - GPU DataFrame Library

Language:C++Apache-2.0802900

HandyRL

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.

Language:PythonMIT28200