notebooks, 一些用于scikit的示例IPython笔记本.zip
需积分: 9 28 浏览量
2019-09-18
03:36:22
上传
评论
收藏 9.94MB ZIP 举报
notebooks.zip （70个子文件） 
notebooks-master 
Bootstrap.ipynb 102KB Parameter search for Extra Trees on the MNIST classificationt task.ipynb 44KB .gitignore 169B dask fold_learn.ipynb 23KB gmm Gaussian likelihood landscape.ipynb 50KB GMM with SGD.ipynb 645KB GMM with PyTorch.ipynb 55KB Model Selection for GMM.ipynb 53KB gmmsgd.py 7KB gradients custom optim.ipynb 27KB Adjusted Variable Importances with Randomized Trees.ipynb 262KB README.md 328B Non IID cross-validation.ipynb 7KB Gradient.ipynb 319KB Attention Keras Attention.ipynb 8KB letor_cluster letor_gridresults.json 109KB letor_gridpoint.py 4KB MSLR Grid Search.ipynb 207KB letor_gridsearch.py 2KB letor_gridresults.py 886B MNIST8M Chunking and Upload to Cloud Blob Storage.ipynb 14KB SGD stuff.ipynb 159KB Clustering Model Selection.ipynb 313B Patch-Based Feature Extraction for Image Classification.ipynb 513KB environment.yml 57B Variable Importance with Completely Randomized Trees.ipynb 397KB Function Approximation.ipynb 21KB Learning to Rank.ipynb 264KB screenshots 
digits.png 129KB topics.png 155KB Numa-aware computation experiments.ipynb 24KB Overfitting linear-model-overfitting.ipynb 48KB nmf_topics.ipynb 5KB Text Classification.ipynb 22KB Saddle Point LBFGS.ipynb 364KB Distributed Learning of Extra Trees with IPython.parallel.ipynb 39KB Numba Parakeet Cython.ipynb 17KB ubuntu-quickstart.sh 1KB Semi-supervised Extra Trees.ipynb 24KB generalization run_mnist.py 7KB cloudstorage.ini.example 90B fmri_vae fmri_model.py 5KB fmri_autoencoder.ipynb 421KB GP overfitting.ipynb 1.42MB Reinforcement Learning Random walk policy evaluation.ipynb 188KB Numpy intro.ipynb 110KB Labeled Faces in the Wild recognition.ipynb 701KB Explained variances.ipynb 59KB representations Unsupervised feature extraction with the Breiman trick.ipynb 222KB Sparse non-linear random projections.ipynb 59KB Entangled Manifolds.ipynb 184KB Autoencoder ELMs.ipynb 298KB MNIST experiments.ipynb 96KB Data Preprocessing for the Learning to Rank example.ipynb 2KB Time Series.ipynb 78KB structure_digits.ipynb 5KB Distributed Aggregate and Join.ipynb 28KB sklearn_demos Language Classification.ipynb 24KB Income classification.ipynb 493KB Income classification - Column Transformer Edition.ipynb 491KB Face recognition.ipynb 565KB fastText.ipynb 9KB Feature Importances.ipynb 152KB Permutation Importances.ipynb 117KB iris.ipynb 291KB language fetch_data.py 4KB Large Scale 2D Clustering.ipynb 2.15MB Large Scale 2D Clustering-1M.ipynb 1.73MB Classifier calibration.ipynb 517KB Gradient Boosting.ipynb 198KB资源评论
