call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return

call_command', 'clearsessions', schedule_type='H') Groups A group example with Kernel density estimation for probability density functions using the Parzen-window technique. Adapted from Sebastian Raschka’s Group example with Parzen-window estimation import numpy from django_q.tasks import async, result_group, delete_group # the estimation function def parzen_estimation(x_samples, point_x, h): k_n = # async them with a group label to the cache backend for w in widths: async(parzen_estimation, sample, x, w, group='parzen', cached=True) # return after 100 results return