Deep Learning with TensorFlow

By Barbara Fusinska

Learn how to use Python and TensorFlow with Deep Learning tasks

SCENARIO 1

Classification task

Introduction to Machine Learning Classification problem

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SCENARIO 2

Logistic Regression

Using logistic regression to the non lineary separable data classification

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SCENARIO 3

Numpy Basics

Introduction to Python numpy package

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SCENARIO 4

Forward propagation

Learn how to build simple neural network using numpy

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SCENARIO 5

Hidden layers

Learn how to build hidden fully connected layers using numpy

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SCENARIO 6

Neural Network Training

Create your first Neural Network training process

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SCENARIO 7

Computational Graph: Core

Introduction to TensorFlow Core

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SCENARIO 8

Optimising the function

Use TensorFlow to optimise the function

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SCENARIO 9

TensorFlow Network Training

Create simple classifying neural network in TensorFlow

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SCENARIO 10

TensorFlow Deep Network Training

Create deep classifying neural network in TensorFlow

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SCENARIO 11

MNIST Dataset

Introduction to MNIST Dataset provided by TensorFlow

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SCENARIO 12

MNIST Simple Neural Network Training

Walkthrough the TensorFlow training process for MNIST dataset

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SCENARIO 13

MNIST Dataset Deep Learning

Build deep network for MNIST Dataset in TensorFlow

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SCENARIO 14

MNIST Simple Neural Network Training Solution

Walkthrough the deep network creation for MNIST dataset

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SCENARIO 15

MNIST Dataset Convolution

Build convolutional network for MNIST Dataset in TensorFlow

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SCENARIO 16

APIs: Hidden layers with tf.layers

Walkthrough the deep network creation for MNIST dataset

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