Related Repositories for scikit-learn-contrib/imbalanced-learn

Repository	⭐ Stars	🍴 Forks	Ratio
scikit-learn-contrib/imbalanced-learn	6,673	330	20.22
tensorflow/tensorflow	2,475	657	3.77
tensorflow/models	2,108	443	4.76
scikit-learn/scikit-learn	2,035	615	3.31
pytorch/pytorch	2,015	293	6.88
dmlc/xgboost	1,840	277	6.64
huggingface/transformers	1,813	256	7.08
slundberg/shap	1,812	110	16.47
TheAlgorithms/Python	1,780	209	8.52
vinta/awesome-python	1,684	204	8.25
josephmisiti/awesome-machine-learning	1,681	277	6.07
ray-project/ray	1,572	110	14.29
fastai/fastai	1,525	187	8.16
aymericdamien/TensorFlow-Examples	1,458	260	5.61
facebookresearch/fastText	1,455	128	11.37
facebookresearch/faiss	1,435	73	19.66
donnemartin/system-design-primer	1,432	126	11.37
google-research/bert	1,414	134	10.55
explosion/spaCy	1,397	121	11.55
streamlit/streamlit	1,375	50	27.50
sindresorhus/awesome	1,372	146	9.40
google/jax	1,337	47	28.45
google-research/google-research	1,300	84	15.48
marcotcr/lime	1,257	83	15.14
openai/gym	1,238	112	11.05
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers	1,233	187	6.59
tiangolo/fastapi	1,227	51	24.06
jakevdp/PythonDataScienceHandbook	1,163	183	6.36
sebastianruder/NLP-progress	1,155	85	13.59
keras-team/keras	1,141	223	5.12
mlflow/mlflow	1,132	84	13.48
jwasham/coding-interview-university	1,128	177	6.37
ageron/handson-ml	1,113	194	5.74
tqdm/tqdm	1,105	35	31.57
donnemartin/data-science-ipython-notebooks	1,102	166	6.64
yunjey/pytorch-tutorial	1,083	148	7.32
automl/auto-sklearn	1,079	66	16.35
fchollet/keras	1,071	224	4.78
pytorch/examples	1,069	162	6.60
google/python-fire	1,062	24	44.25
terryum/awesome-deep-learning-papers	1,061	114	9.31
facebookresearch/Detectron	1,054	99	10.65
microsoft/DeepSpeed	1,047	49	21.37
pandas-dev/pandas	1,045	199	5.25
RaRe-Technologies/gensim	1,039	96	10.82
ageitgey/face_recognition	1,039	90	11.54
gradio-app/gradio	1,031	31	33.26
3b1b/manim	1,015	38	26.71
eriklindernoren/ML-From-Scratch	1,010	121	8.35
blue-yonder/tsfresh	1,008	53	19.02
hyperopt/hyperopt	992	70	14.17
modin-project/modin	992	28	35.43
plotly/dash	986	36	27.39
catboost/catboost	986	59	16.71
allenai/allennlp	983	79	12.44
jlevy/the-art-of-command-line	962	68	14.15
spotify/annoy	959	43	22.30
dask/dask	956	60	15.93
BVLC/caffe	955	171	5.58
facebook/prophet	955	72	13.26
dennybritz/reinforcement-learning	948	127	7.46
tesseract-ocr/tesseract	939	49	19.16
iterative/dvc	938	36	26.06
hwchase17/langchain	926	59	15.69
python/cpython	926	126	7.35
rwightman/pytorch-image-models	924	68	13.59
tensorflow/tensor2tensor	923	69	13.38
statsmodels/statsmodels	919	99	9.28
HarisIqbal88/PlotNeuralNet	919	43	21.37
scrapy/scrapy	919	100	9.19
facebookresearch/detectron2	912	69	13.22
faif/python-patterns	909	92	9.88
Microsoft/LightGBM	904	105	8.61
rasbt/mlxtend	904	63	14.35
apache/spark	898	237	3.79
onnx/onnx	896	35	25.60
lutzroeder/netron	893	29	30.79
aleju/imgaug	875	74	11.82
matterport/Mask_RCNN	867	116	7.47
pytorch/fairseq	859	73	11.77
eugeneyan/applied-ml	857	52	16.48
d2l-ai/d2l-en	856	84	10.19
EthicalML/awesome-production-machine-learning	854	50	17.08
kamranahmedse/developer-roadmap	847	50	16.94
jtoy/awesome-tensorflow	845	92	9.18
github/gitignore	845	204	4.14
yzhao062/pyod	844	55	15.35
numpy/numpy	837	113	7.41
spotify/luigi	836	57	14.67
oxford-cs-deepnlp-2017/lectures	831	92	9.03
satwikkansal/wtfpython	829	33	25.12
scutan90/DeepLearning-500-questions	825	133	6.20
UKPLab/sentence-transformers	825	52	15.87
pola-rs/polars	825	35	23.57
fchollet/deep-learning-with-python-notebooks	824	111	7.42
dmlc/dgl	822	71	11.58
ggerganov/llama.cpp	819	33	24.82
openai/gpt-2	816	60	13.60
PyTorchLightning/pytorch-lightning	814	66	12.33
DistrictDataLabs/yellowbrick	809	42	19.26