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Master Classes

Deep Learning

Only for Members

The following list is the links to the classrooms of the Deep Learning.

free eng web

Study guide for Introducation to Deep Learning

The following information provides study guideline to help people study Deep Learning by themselves. These Youtube videos will provide enough information to people so they can get ready to take Andrew Ng's Deep Learning Specialist Program. Sedisbus Education provides limited number of online classes to learn together the topics. For more information about it please contact Sedibus Education.

1. Applications of Deep Learning

(Week 1)

2. Let's try to hear what a Google employer talks about Deep Learning

(Week 2)

3. Let's learn about the foundation concept of Deep Learning

4. Now let,s go back to the Google employer's talk and see how much more you understood.

(Week 5)

5. Let's set up  the system for actual coding 

(Week 6)

6. Let's build an application

(Week 7)

7. Let's build more advanced one (optional)

How to Classify Photos of Dogs and Cats (with 97% accuracy)

https://machinelearningmastery.com/how-to-develop-a-convolutional-neural-network-to-classify-photos-of-dogs-and-cats/

 

Image Classifier - Cats🐱 vs Dogs🐶

Leveraging Convolutional Neural Networks (CNNs) and Google Colab’s Free GPU

https://towardsdatascience.com/image-classifier-cats-vs-dogs-with-convolutional-neural-networks-cnns-and-google-colabs-4e9af21ae7a8

A friendly introduction to Convolutional Neural Networks and Image Recognition

https://www.youtube.com/watch?v=2-Ol7ZB0MmU

Statistics for Deep Learning

     https://www.youtube.com/watch?v=tcusIOfI_GM

Deep Learning ( Andrew Ng)

Tuning Process (C2W3L01)

     https://www.youtube.com/watch?v=AXDByU3D1hA

 

Using an Appropriate Scale (C2W3L02)

     https://www.youtube.com/watch?v=cSoK_6Rkbfg

 

Hyperparameter Tuning in Practice (C2W3L03)

     https://www.youtube.com/watch?v=wKkcBPp3F1Y

 

Normalizing Activations in a Network (C2W3L04)

     Normalizing Activations in a Network (C2W3L04)

 

Why Regularization Reduces Overfitting (C2W1L05)

     https://www.youtube.com/watch?v=NyG-7nRpsW8

Dropout Regularization (C2W1L06)

     https://www.youtube.com/watch?v=D8PJAL-MZv8&t=53s

Understanding Dropout (C2W1L07)

     https://www.youtube.com/watch?v=ARq74QuavAo

Other Regularization Methods (C2W1L08)

     https://www.youtube.com/watch?v=BOCLq2gpcGU

Normalizing Inputs (C2W1L09)

     https://www.youtube.com/watch?v=FDCfw-YqWTE

Vanishing/Exploding Gradients (C2W1L10)

     https://www.youtube.com/watch?v=qhXZsFVxGKo

Weight Initialization in a Deep Network (C2W1L11)

     https://www.youtube.com/watch?v=s2coXdufOzE&t=2s

Weight Initialization explained | A way to reduce the vanishing gradient problem

     https://www.youtube.com/watch?v=8krd5qKVw-Q

Numerical Approximations of Gradients (C2W1L12)

     https://www.youtube.com/watch?v=y1xoI7mBtOc

Gradient Checking (C2W1L13)

     https://www.youtube.com/watch?v=QrzApibhohY

Gradient Checking Implementation Notes (C2W1L14)

    https://www.youtube.com/watch?v=4Ct3Yujl1dk

Mini Batch Gradient Descent (C2W2L01)

    https://www.youtube.com/watch?v=4qJaSmvhxi8

Understanding Mini-Batch Gradient Dexcent (C2W2L02)

    https://www.youtube.com/watch?v=-_4Zi8fCZO4

Exponentially Weighted Averages (C2W2L03)

    https://www.youtube.com/watch?v=lAq96T8FkTw

Understanding Exponentially Weighted Averages (C2W2L04)

    https://www.youtube.com/watch?v=NxTFlzBjS-4

Bias Correction of Exponentially Weighted Averages (C2W2L05)

    https://www.youtube.com/watch?v=lWzo8CajF5s

Gradient Descent With Momentum (C2W2L06)

    https://www.youtube.com/watch?v=k8fTYJPd3_I

RMSProp (C2W2L07)

    https://www.youtube.com/watch?v=_e-LFe_igno

Adam Optimization Algorithm (C2W2L08)

    https://www.youtube.com/watch?v=JXQT_vxqwIs

Learning Rate Decay (C2W2L09)

    https://www.youtube.com/watch?v=QzulmoOg2JE

Tuning Process (C2W3L01)

    https://www.youtube.com/watch?v=AXDByU3D1hA

Using an Appropriate Scale (C2W3L02)

    https://www.youtube.com/watch?v=cSoK_6Rkbfg

Hyperparameter Tuning in Practice (C2W3L03)

    https://www.youtube.com/watch?v=wKkcBPp3F1Y

Normalizing Activations in a Network (C2W3L04)

    https://www.youtube.com/watch?v=tNIpEZLv_eg

Fitting Batch Norm Into Neural Networks (C2W3L05)

    https://www.youtube.com/watch?v=em6dfRxYkYU

Why Does Batch Norm Work? (C2W3L06)

    https://www.youtube.com/watch?v=nUUqwaxLnWs

Batch Norm At Test Time (C2W3L07)

    https://www.youtube.com/watch?v=5qefnAek8OA

Softmax Regression (C2W3L08)

    https://www.youtube.com/watch?v=LLux1SW--oM

Training Softmax Classifier (C2W3L09)

    https://www.youtube.com/watch?v=ueO_Ph0Pyqk

TensorFlow (C2W3L11)

    https://www.youtube.com/watch?v=S9ElPZupUsE

Improving Model Performance (C3W1L01)

    https://www.youtube.com/watch?v=dFX8k1kXhOw

Orthogonalization (C3W1L02 )

    https://www.youtube.com/watch?v=UEtvV1D6B3s

Single Number Evaluation Metric (C3W1L03)

    https://www.youtube.com/watch?v=sofffBNhVSo

Satisficing and Optimizing Metrics (C3W1L04)

    https://www.youtube.com/watch?v=BH9mlmdXzzI

Train/Dev/Test Set Distributions (C3W1L05)

    https://www.youtube.com/watch?v=M3qpIzy4MQk

Sizeof Dev and Test Sets (C3W1L06)

    https://www.youtube.com/watch?v=_Fe5kKmFieg

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