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Udemy - From 0 to 1 Machine Learning, NLP & Python-Cut to the Chase (2015)

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种子名称： Udemy - From 0 to 1 Machine Learning, NLP & Python-Cut to the Chase (2015)
文件类型：视频
文件数目： 28个文件
文件大小： 2.87 GB
收录时间： 2016-9-2 22:53
已经下载： 3次
资源热度： 118
最近下载： 2024-12-18 04:16

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Udemy - From 0 to 1 Machine Learning NLP & Python-Cut to the Chase 2015

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Udemy - From 0 to 1 Machine Learning, NLP & Python-Cut to the Chase (2015).torrent

11_-_Regression_as_a_form_of_supervised_learning/23_-_Regression_Introduced_-_Linear_and_Logistic_Regression.mp499.03MB

12_-_Natural_Language_Processing_and_Python/28_-_Put_it_to_work_-_News_Article_Clustering_with_K-Means_and_TF-IDF.mp4107.16MB

12_-_Natural_Language_Processing_and_Python/25_-_Put_it_to_work_-_News_Article_Classification_using_K-Nearest_Neighbors.mp4148MB

12_-_Natural_Language_Processing_and_Python/24_-_A_Serious_NLP_Application_-_Text_Auto_Summarization_using_Python.mp491.1MB

12_-_Natural_Language_Processing_and_Python/26_-_Put_it_to_work_-_News_Article_Classification_using_Naive_Bayes_Classifier.mp4140.68MB

12_-_Natural_Language_Processing_and_Python/27_-_Document_Distance_using_TF-IDF.mp479.09MB

05_-_K-Nearest_Neighbors/14_-_K-Nearest_Neighbors_-_A_few_wrinkles.mp4114.72MB

05_-_K-Nearest_Neighbors/13_-_K-Nearest_Neighbors.mp488.65MB

01_-_Introduction/01_-_What_this_course_is_about.mp4125.09MB

09_-_Dimensionality_Reduction/20_-_Principal_Component_Analysis.mp4124.77MB

09_-_Dimensionality_Reduction/19_-_Dimensionality_Reduction.mp4127.51MB

03_-_Classification_-_A_form_of_supervised_learning/06_-_Classification_-_Problems_and_Techniques.mp4127.5MB

03_-_Classification_-_A_form_of_supervised_learning/07_-_Bias_Variance_Trade-off.mp473.82MB

04_-_Naive_Bayes_Classifier/10_-_Naive_Bayes_Classifier.mp474.01MB

04_-_Naive_Bayes_Classifier/12_-_Naive_Bayes_Classifier_-_Application_to_spam_detection.mp468.76MB

04_-_Naive_Bayes_Classifier/11_-_Naive_Bayes_Classifier_-_An_example.mp495.9MB

04_-_Naive_Bayes_Classifier/08_-_Random_Variables.mp4119.2MB

04_-_Naive_Bayes_Classifier/09_-_Bayes_Theorem.mp483.68MB

02_-_Jump_right_in_-_Machine_learning_for_Spam_detection/03_-_Plunging_In_-_Machine_Learning_Approaches_to_Spam_Detection.mp4121.81MB

02_-_Jump_right_in_-_Machine_learning_for_Spam_detection/05_-_Get_the_Lay_of_the_Land_-_Types_of_Machine_Learning_Problems.mp4120.06MB

02_-_Jump_right_in_-_Machine_learning_for_Spam_detection/02_-_Machine_Learning_-_Why_should_you_jump_on_the_bandwagon.mp4107.64MB

02_-_Jump_right_in_-_Machine_learning_for_Spam_detection/04_-_Spam_Detection_with_Machine_Learning_Continued.mp4117.09MB

06_-_Support_Vector_Machines/16_-_Support_Vector_Machines_-_Maximum_Margin_Hyperplane_and_Kernel_Trick.mp4120.83MB

06_-_Support_Vector_Machines/15_-_Support_Vector_Machines_Introduced.mp467.69MB

08_-_Association_Detection/18_-_Association_Rules_Learning.mp471.87MB

07_-_Clustering_as_a_form_Unsupervised_learning/17_-_Clustering_-_Problems_and_Techniques.mp4119MB

10_-_Artificial_Neural_Networks/22_-_Perceptron_-_How_it_works.mp457.64MB

10_-_Artificial_Neural_Networks/21_-_Artificial_Neural_Networks_I_Perceptron_introduced_via_Support_Vector_Machines_.mp4145.07MB