{"payload":{"header_redesign_enabled":false,"results":[{"id":"125473179","archived":false,"color":"#DA5B0B","followers":9,"has_funding_file":false,"hl_name":"jalajthanaki/Customer_churn_analysis","hl_trunc_description":"Predicting customer churn using scikit-learn","language":"Jupyter Notebook","mirror":false,"owned_by_organization":false,"public":true,"repo":{"repository":{"id":125473179,"name":"Customer_churn_analysis","owner_id":12840374,"owner_login":"jalajthanaki","updated_at":"2018-03-16T06:28:41.839Z","has_issues":true}},"sponsorable":false,"topics":["machine-learning","predictive-analysis","telecoms","customer-analytics"],"type":"Public","help_wanted_issues_count":0,"good_first_issue_issues_count":0,"starred_by_current_user":false}],"type":"repositories","page":1,"page_count":1,"elapsed_millis":67,"errors":[],"result_count":1,"facets":[],"protected_org_logins":[],"topics":null,"query_id":"","logged_in":false,"sign_up_path":"/signup?source=code_search_results","sign_in_path":"/login?return_to=https%3A%2F%2Fgithub.com%2Fsearch%3Fq%3Drepo%253Ajalajthanaki%252FCustomer_churn_analysis%2B%2Blanguage%253A%2522Jupyter%2BNotebook%2522","metadata":null,"csrf_tokens":{"/jalajthanaki/Customer_churn_analysis/star":{"post":"ssxOWtxCXD4c-xu7e1PytLINEcXrdjAgUVk9Y6Tx5c3jq4dICLkLQeQLAhWjsyAsXZFkN1SOqfCdm9liHXeQnA"},"/jalajthanaki/Customer_churn_analysis/unstar":{"post":"vpZeZ_yADK4cdsVeJESZX9Mcze88pQtm9k7Y0MMnONaB2FA10YCS9TSmai6D40zt7TxE9GZmdhfAP02T8TeMRw"},"/sponsors/batch_deferred_sponsor_buttons":{"post":"evJ6DLXVqMGPYP25WEq-yrT7q_nt1C-PDPFFF2_N3l_clDt4vNgEN-Qt3r-haUDlvGtZGAjR6CuDKYHZWpJhAA"}}},"title":"Repository search results"}