使用Python进行机器学习：用于理解核心概念的小型机器学习项目。 给星星:glowing_star:如果有帮助的话。 奖金：面试银行来了..！-源码

[{"title":"（ 97 个子文件 734KB ） 使用Python进行机器学习：用于理解核心概念的小型机器学习项目。 给星星:glowing_star:如果有帮助的话。 奖金：面试银行来了..！-源码","children":[{"title":"Machine-Learning-with-Python-master","children":[{"title":"Anamoly_Detection_notes.md <span style='color:#111;'> 2.79KB </span>","children":null,"spread":false},{"title":"k_nearest_neighbors","children":[{"title":"data.py <span style='color:#111;'> 3.06KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 3.41KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.14KB </span>","children":null,"spread":false},{"title":"Understanding the algorithm.md <span style='color:#111;'> 2.08KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 3.87KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 2.56KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"decision_trees","children":[{"title":"data.py <span style='color:#111;'> 1.08KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 3.51KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.34KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 4.30KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 720B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":".github","children":[{"title":"ISSUE_TEMPLATE","children":[{"title":"bug_report.md <span style='color:#111;'> 834B </span>","children":null,"spread":false},{"title":"feature_request.md <span style='color:#111;'> 595B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"sonar_clf_rf.py <span style='color:#111;'> 7.26KB </span>","children":null,"spread":false},{"title":"logistic_regression_banking","children":[{"title":"binary_logisitic_regression.py <span style='color:#111;'> 2.36KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 912B </span>","children":null,"spread":false},{"title":"banking.csv <span style='color:#111;'> 4.62MB </span>","children":null,"spread":false}],"spread":true},{"title":"logistic_regression","children":[{"title":"data.py <span style='color:#111;'> 3.61KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 1.10KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 2.24KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 2.14KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 5.21KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"k_means_clustering","children":[{"title":"data.py <span style='color:#111;'> 243B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 4.76KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"Understanding the algorithm.md <span style='color:#111;'> 3.21KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 6.02KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 598B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"naive_bayes_classfier","children":[{"title":"naivebayesclassifier.py <span style='color:#111;'> 749B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 1.87KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 2.15KB </span>","children":null,"spread":false}],"spread":true},{"title":"mnist-deep-learning.py <span style='color:#111;'> 941B </span>","children":null,"spread":false},{"title":"recommender_systems","children":[{"title":"data.py <span style='color:#111;'> 957B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 2.42KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.61KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 3.41KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 843B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"use_cases_insurnace.md <span style='color:#111;'> 3.64KB </span>","children":null,"spread":false},{"title":"working_with_data","children":[{"title":"comma_delimited_stock_prices.csv <span style='color:#111;'> 118B </span>","children":null,"spread":false},{"title":"data.py <span style='color:#111;'> 4.08KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 9.17KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 3.45KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 13.98KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 3.83KB </span>","children":null,"spread":false}],"spread":false},{"title":"stocks.txt <span style='color:#111;'> 343.52KB </span>","children":null,"spread":false}],"spread":true},{"title":"scripts","children":[{"title":"install_requirements.sh <span style='color:#111;'> 45B </span>","children":null,"spread":false}],"spread":false},{"title":"requirements.txt <span style='color:#111;'> 718B </span>","children":null,"spread":false},{"title":"natural_language_processing","children":[{"title":"data.py <span style='color:#111;'> 1.64KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 6.25KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 7.04KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 1.67KB </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"helpers","children":[{"title":"linear_algebra.py <span style='color:#111;'> 3.32KB </span>","children":null,"spread":false},{"title":"gradient_descent.py <span style='color:#111;'> 5.41KB </span>","children":null,"spread":false},{"title":"machine_learning.py <span style='color:#111;'> 1.22KB </span>","children":null,"spread":false},{"title":"probabilty.py <span style='color:#111;'> 3.80KB </span>","children":null,"spread":false},{"title":"stats.py <span style='color:#111;'> 6.48KB </span>","children":null,"spread":false}],"spread":false},{"title":"Understanding Vanishing Gradient.md <span style='color:#111;'> 3.88KB </span>","children":null,"spread":false},{"title":"neural_network","children":[{"title":"data.py <span style='color:#111;'> 713B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 3.43KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 2.27KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 3.58KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 799B </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"CONTRIBUTING.md <span style='color:#111;'> 4.12KB </span>","children":null,"spread":false},{"title":"Understanding SQL Queries.md <span style='color:#111;'> 5.58KB </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"multiple_regression","children":[{"title":"data.py <span style='color:#111;'> 4.63KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 3.31KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 2.20KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 5.18KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 5.61KB </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"telecom_churn_prediction.py <span style='color:#111;'> 2.08KB </span>","children":null,"spread":false},{"title":"interview_prep.md <span style='color:#111;'> 21.81KB </span>","children":null,"spread":false},{"title":"hypothesis_inference.py <span style='color:#111;'> 5.84KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 7.14KB </span>","children":null,"spread":false},{"title":"NN_churn_prediction.py <span style='color:#111;'> 1.97KB </span>","children":null,"spread":false},{"title":"simple_linear_regression","children":[{"title":"data.py <span style='color:#111;'> 2.02KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 1.16KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 1016B </span>","children":null,"spread":false}],"spread":false},{"title":"network_analysis","children":[{"title":"data.py <span style='color:#111;'> 638B </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 5.68KB </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 645B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-35.pyc <span style='color:#111;'> 5.79KB </span>","children":null,"spread":false},{"title":"data.cpython-35.pyc <span style='color:#111;'> 902B </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"CODE_OF_CONDUCT.md <span style='color:#111;'> 3.28KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 1.17KB </span>","children":null,"spread":false},{"title":"friendster_network.py <span style='color:#111;'> 6.06KB </span>","children":null,"spread":false},{"title":"LDA scikit-learn","children":[{"title":"load20newsgroups.py <span style='color:#111;'> 174B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"nmf_lda_scikitlearn.cpython-34.pyc <span style='color:#111;'> 607B </span>","children":null,"spread":false},{"title":"load20newsgroups.cpython-34.pyc <span style='color:#111;'> 376B </span>","children":null,"spread":false},{"title":"preprocess.cpython-34.pyc <span style='color:#111;'> 652B </span>","children":null,"spread":false}],"spread":false},{"title":"nmf_lda_scikitlearn.py <span style='color:#111;'> 403B </span>","children":null,"spread":false},{"title":"preprocess.py <span style='color:#111;'> 666B </span>","children":null,"spread":false},{"title":"displaytopics.py <span style='color:#111;'> 501B </span>","children":null,"spread":false}],"spread":false},{"title":"regression_intro.py <span style='color:#111;'> 2.72KB </span>","children":null,"spread":false},{"title":"hparams_grid_search_keras_nn.py <span style='color:#111;'> 2.75KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]