إنشاء حساب
الرئيسية
الكورسات
تعلم الآلة
دورة تعلم الآلة - مقدمة | من تقديم البروفيسور سوديشنا ساركار
Tutorial II

Tutorial II

دورة تعلم الآلة - مقدمة | من تقديم البروفيسور سوديشنا ساركار

الدرس السابق الدرس التالي

محتوى الكورس

جميع الدروس
47 درس
03:25 Introduction
28:44 Introduction
24:55 Different Types of Learning
33:25 Hypothesis Space and Inductive Bias
22:13 Evaluation and Cross-Validation
42:17 Tutorial I
35:33 Linear Regression
24:25 Introduction to Decision Trees
29:24 Learning Decision Tree
28:04 Overfitting
25:30 Python Exercise on Decision Tree and Linear Regression
25:14 Tutorial II
36:38 k-Nearest Neighbour
26:02 Feature Selection
21:26 Feature Extraction
25:14 Collaborative Filtering
18:34 Python Exercise on kNN and PCA
38:01 Tutorial III
28:19 mod03lec18
29:04 Bayesian Learning
27:10 Naive Bayes
33:32 Bayesian Network
17:38 Python Exercise on Naive Bayes
40:01 Tutorial IV
20:40 Logistic Regression
32:05 Introduction Support Vector Machine
16:48 SVM: The Dual Formulation
18:24 SVM: Maximum Margin with Noise
28:01 Nonlinear SVM and Kernel Function
11:22 SVM: Solution to the Dual Problem
29:17 Python Exercise on SVM
30:14 Introduction
35:33 Multilayer Neural Network
35:08 Neural Network and Backpropagation Algorithm
35:48 Deep Neural Network
36:25 Python Exercise on Neural Network
41:13 Tutorial VI
32:59 Introduction to Computational Learning Theory
14:39 Sample Complexity: Finite Hypothesis Space
21:09 VC Dimension
37:15 Introduction to Ensembles
31:45 Bagging and Boosting
23:56 Introduction to Clustering
33:07 Kmeans Clustering
17:26 Agglomerative Hierarchical Clustering
40:21 Python Exercise on kmeans clustering
41:26 Tutorial08