BasicsofNeuralNetworkProgramming

BinaryClassificationdeeplearning.ai

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1 (cat) vs 0 (non cat)

255 134 93 22123 94 83 234 44 187 3034 76 232 12467 83 194 142

255 134 202 22123 94 83 434 44 187 19234 76 232 3467 83 194 94

255 231 42 22123 94 83 234 44 187 9234 76 232 12467 83 194 202

RedGreen

Blue

Binary Classification

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Notation

Basics of NeuralNetwork Programming

LogisticRegressiondeeplearning.ai

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Logistic Regression

Basics of NeuralNetwork Programming

LogisticRegression

cost functiondeeplearning.ai

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Logistic Regression cost function•

Loss (error) function:

Basics of NeuralNetwork Programming

LogisticRegression

cost functiondeeplearning.ai

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Logistic Regression cost function•

Loss (error) function:

BasicsofNeuralNetworkProgramming

GradientDescentdeeplearning.ai

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Gradient DescentRecap: !" = % &'( + * , % + = ,

,-./0

1 &, * =1456

78,ℒ(!" 7 , !(7)) =− 1

456

78,!(7) log !" 7 + (1 − !(7)) log(1 − !" 7 )

Want to find &, * that minimize 1 &, *

*

1 &, *

&

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Gradient Descent

&

BasicsofNeuralNetworkProgramming

LogisticRegressionasaNeuralNetworkdeeplearning.ai

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Logistic Regression as a Neural Network!" = % &'( + * ,where % + = ,

,-./0

Basics of NeuralNetwork Programming

Derivativesdeeplearning.ai

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Intuition about derivatives

Basics of NeuralNetwork Programming

More derivativesexamplesdeeplearning.ai

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Intuition about derivatives

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More derivative examples

Basics of NeuralNetwork Programming

Computation Graphdeeplearning.ai

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Computation Graph

Basics of NeuralNetwork Programming

Derivatives with aComputation Graphdeeplearning.ai

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Computing derivatives

611 33

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Computing derivatives

611 33

Basics of NeuralNetwork Programming

LogisticRegression

Gradient descentdeeplearning.ai

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Logistic regression recap

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Logistic regression derivatives

b

Basics of NeuralNetwork Programming

Gradient descenton m examplesdeeplearning.ai

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Logistic regression on m examples

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Logistic regression on m examples

Basics of NeuralNetwork Programming

Vectorizationdeeplearning.ai

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What is vectorization?

Basics of NeuralNetwork Programming

More vectorizationexamplesdeeplearning.ai

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Neural network programming guidelineWhenever possible, avoid explicit for-loops.

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Neural network programming guidelineWhenever possible, avoid explicit for-loops.

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Vectors and matrix valued functionsSay you need to apply the exponential operation on every element of amatrix/vector.

u[i]=math.exp(v[i])

u = np.zeros((n,1)) for i in range(n):

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Logistic regression derivativesJ = 0, dw1 = 0, dw2 = 0, db = 0

for i = 1 ton:

Basics of NeuralNetwork Programming

VectorizingLogistic

Regressiondeeplearning.ai

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Vectorizing Logistic Regression

Basics of NeuralNetwork Programming

Vectorizing LogisticRegression’s

GradientComputation

deeplearning.ai

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Vectorizing Logistic Regression

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Implementing Logistic Regression

for i = 1 tom:

BasicsofNeuralNetworkProgramming

BroadcastinginPythondeeplearning.ai

Broadcasting example

cal = A.sum(axis = 0)percentage = 100*A/(cal.reshape(1,4))

Apples Beef Eggs PotatoesCarb

Fat

56.0 0.0 4.4 68.01.2 104.0 52.0 8.01.8 135.0 99.0 0.9

Protein

CaloriesfromCarbs,Proteins,Fatsin100gofdifferentfoods:

101 102 103204 205 206

1 2 34 5 6

100200+ =

101 202 303104 205 306

100 200 3001 2 34 5 6 + =

1234

100101102103104

+ =

Broadcasting example

General Principle

BasicsofNeuralNetworkProgramming

Explanationoflogisticregressioncostfunction

(Optional)deeplearning.ai

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Logistic regression cost function

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If$ = 1: ( $ ) = $*If$ = 0: ( $ ) = 1 − $*

Logistic regression cost function

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Cost on m examples