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Introduction to Deep Learning and Neural Networks.
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Bedanta Bikash Borah
July 24, 2018
Education
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Introduction to Deep Learning and Neural Networks.
Bedanta Bikash Borah
July 24, 2018
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Transcript
Introduction to Deep Learning and Neural Networks. Bedanta Bikash Borah
@iamBedant
None
None
Agenda 1. What is Deep Learning? 2. Why Deep Learning
is taking off? 3. How Deep Learning works? 4. Training. 5. Example MNIST. 6. Code Sample. 7. Few extra concepts.
Deep Learning The term Deep Learning refers to training very
large Neural Network
What is Neural Network? House Size (X) Price (Y) 500
5 Laks 600 8 Laks 700 9 Laks 800 13 Laks 900 12 Laks 1100 18 Laks 1200 20 Laks
Housing Price Prediction 0 laks 5 laks 10 laks 15
laks 20 laks 000 sq ft 300 sq ft 600 sq ft 900 sq ft 1200 sq ft What is Neural Network?
What is Neural Network? x Y Size of the House
Price of the House Neuron Function F Input Output
What is Neural Network? Size No of bedrooms Locality Society
Y Family Size Walkability School/Market Quality
What is Neural Network? X1 X2 X3 X4 Y Size
No of bedrooms Locality Society
Deep Neural Network
Why DeepLearning taking off? Deep Neural Network Medium Neural Network
Traditional ML Algorithm Data Performance Not well defined
Why DeepLearning taking off? 1. Data 2. Computation 3. Algorithm
How DeepLearning Works? X1 X2 X3 X4 Y
How DeepLearning Works? X1 X2 X3 X4 Y f W1
W2 W3 W4 X1* W1 + X2 * W2 + X3 * W3 +X4 * W4 Z f( )= Relu (x) or Sigmoid(x) *ignoring bias for simplification Z =
How DeepLearning Works?
How DeepLearning Works? X1 X2 X3 X4 Y
Interviewer: What is your biggest strength? Me: I am an
expert in machine learning. Interviewer: What’s 9 + 10? Me: It’s 3. Interviewer: Nowhere near. It’s 19. Me: It’s 16. Interviewer: Wrong. It’s still 19 Me: It’s 18. Interviewer: No. It’s 19 Me: It’s 19. Interviewer: You’re hired
Training X1 X2 X3 X4 Y Y’ Random Initialisation
Training 1.Quadratic cost 2.Cross-entropy cost 3.Exponential cost Cost Function:
Training Grad Gradient Descent
Training Learning Rate (alpha)
Training Large Learning rate
Training Learning Rate (alpha)
Training New Weights = Existing Weights Learning Rate - *
Gradient ( )
Interviewer: What is your biggest strength? Me: I am an
expert in machine learning. Interviewer: What’s 9 + 10? Me: It’s 3. Interviewer: Nowhere near. It’s 19. Me: It’s 16. Interviewer: Wrong. It’s still 19 Me: It’s 18. Interviewer: No. It’s 19 Me: It’s 19. Interviewer: You’re hired.
Example MNIST
MNIST 60,000 training samples 10,000 test samples
MNIST
MNIST = 28 x 28 = 784
MNIST Softmax Image Vector Neural Network Layers
MNIST Softmax Image Vector Neural Network Layers
MNIST Softmax Image Vector Neural Network Layers
MNIST Softmax Image Vector Neural Network Layers
MNIST Softmax Image Vector Neural Network Layers
MNIST **from three blue one brown’s “But, what is a
neural network?” video**
Talk is cheap show me the code.
Advanced MNIST CNN (convolutional neural network)
Interviewer: What is your biggest strength? Me: I am an
expert in machine learning. Interviewer: What’s 9 + 10? Me: It’s 3. Interviewer: Nowhere near. It’s 19. Me: It’s 16. Interviewer: Wrong. It’s still 19 Me: It’s 18. Interviewer: No. It’s 19 Me: It’s 19. Interviewer: You’re hired.
Interviewer: What is your biggest strength? Me: I am an
expert in machine learning. Interviewer: What’s 9 + 10? Me: It’s 3. Interviewer: Nowhere near. It’s 19. Me: It’s 16. Interviewer: Wrong. It’s still 19 Me: It’s 18. Interviewer: No. It’s 19 Me: It’s 19. Interviewer: What’s 20 + 10? Me: It’s 19
Advanced MNIST Overfitting (Regularization, Dropout)
Extras
Reference https://github.com/iamBedant/CMRIT-Deeplearning-TechTalk-Demo Simple MNIST Example https://github.com/iamBedant/TensoreFlowLite Android TFLite Example Others:
https://www.tensorflow.org/ https://keras.io/
Thank You !!! @iamBedant