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Sotheara Kang

Sotheara Kang

We follow the goal of MOOC. We are encouraged to share all useful video tutorials to make everyone to be professional in your interested area. *** Follow us *** to see more courses.

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4.4 Machine Learning Gradient Descent in Practice II - Learning Rate 8:58
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4.4 Machine Learning Gradient Descent in Practice II - Learning Rate

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4.3 Machine Learning Gradient Descent in Practice I - Feature Scaling 8:52
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4.3 Machine Learning Gradient Descent in Practice I - Feature Scaling

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4.2  Machine Learning Gradient Descent for Multiple Variable 5:05
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4.2 Machine Learning Gradient Descent for Multiple Variable

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4.1 Machine Learning Multiple Features 8:22
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4.1 Machine Learning Multiple Features

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3.6 Machine Learning Inverse and Transpose 11:13
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3.6 Machine Learning Inverse and Transpose

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6.7 Machine Learning Multiclass Classification, One-vs-all 6:15
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6.7 Machine Learning Multiclass Classification, One-vs-all

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6.6 Machine Learning Advanced Optimization 14:07
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6.6 Machine Learning Advanced Optimization

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6.5 Machine Learning Simplified Cost Function and Gradient Descent 10:15
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6.5 Machine Learning Simplified Cost Function and Gradient Descent

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6.4  Machine Learning Cost Function 11:26
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6.4 Machine Learning Cost Function

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6.3 Machine Learning Decision Boudary 14:50
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6.3 Machine Learning Decision Boudary

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6.2 Machine Learning Hypothesis Representation 7:25
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6.2 Machine Learning Hypothesis Representation

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6.1 Machine Learning Classification 8:09
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6.1 Machine Learning Classification

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5.7 Machine Learning Working on and Submitting Programming Excercises 3:33
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5.7 Machine Learning Working on and Submitting Programming Excercises

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5.6 Machine Learning Vectorization 13:48
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5.6 Machine Learning Vectorization

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5.5 Machine Learning Control Statement, for, while, if statement 12:56
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5.5 Machine Learning Control Statement, for, while, if statement

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8.7 Machine Learning Multiclass Classfication 3:51
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8.7 Machine Learning Multiclass Classfication

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8.6 Machine Learning Examples and Intuitions II 10:20
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8.6 Machine Learning Examples and Intuitions II

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8.5 Machine Learning Exampes and Intuitions I 7:16
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8.5 Machine Learning Exampes and Intuitions I

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8.4 Machine Learning Model Representation II 11:46
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8.4 Machine Learning Model Representation II

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8.3 Machine Learning Model Representation I 12:01
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8.3 Machine Learning Model Representation I

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8.2 Machine Learning Neurons and the Brain 7:47
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8.2 Machine Learning Neurons and the Brain

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8.1 Machine Learning Non-Linear Hypotheses 9:36
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8.1 Machine Learning Non-Linear Hypotheses

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7.4 Machine Learning Regularized Logistic Regression 8:34
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7.4 Machine Learning Regularized Logistic Regression

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7.3 Machine Learning Regularized Linear Regression 10:40
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7.3 Machine Learning Regularized Linear Regression

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