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Tensorflow 2 & Keras:Deep Learning & Artificial Intelligence

Deep Learning & Artificial Intelligence with Tensorflow 2 & Keras, Neural Networks, GANs,Autoencoders, Deep Learning A-Z
Instructor:
Goeduhub Technologies
65 students enrolled
English [Auto]
Complete Understanding of TensorFlow 2 (Google’s Deep Learning Framework) from the Scratch
Keras API to quickly build models that run on Tensorflow 2
Learn How Neural Network works
Understand Backpropagation, Forward Propogation, Gradient Descent
Artificial Neural Networks (ANNs)
Convolutional Neural Networks (CNNs)
Perform Image Classification with Convolutional Neural Networks
Image Recognition
Recurrent Neural Networks (RNNs)
Transfer Learning
Create Generative Adversarial Networks (GANs) with TensorFlow
Autoencoders
Generative Deep Learning - Neural Style Transfer
Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Welcome to Deep Learning and Artificial Intelligence with Tensorflow 2 and Keras API Course.

This course includes how to work with tensorflow 2 and creates Deep Learning applications with tensorflow 2 and Keras.

This course guide you how to work with google colab, all the hands on work done in google colab.

Many Projects included in this course like MNIST Digits Classification, MNIST Fashion data classification, Cat and Dog images Classification, Facial Expression Recognition, Leaf disease recognition, Generate Images with DCGANs(Deep Convolutional Generative Adversarial Networks) with Keras, Denoising autoencoders with Keras, TensorFlow, and Deep Learning etc.

Generative Deep Learning – Neural Style Transfer also included in this course.

For every lecture reference notes and code file is attached in this course.

Tensorflow is an open source machine library, and is one of the most widely used frameworks for deep learning.

Google released a new version of their TensorFlow deep learning library (TensorFlow 2) that integrated the Keras API directly and promoted this interface as the default or standard interface for deep learning development on the platform.

This course includes various topics –

  • Complete Understanding of TensorFlow 2.0 (Google’s Deep Learning Framework)

    from the Scratch

  • Keras API to quickly build models that run on Tensorflow 2

  • Learn How Neural Network works

  • Understand Backpropagation, Forward Propogation, Gradient Descent

  • Artificial Neural Networks (ANNs)

  • Convolutional Neural Networks (CNNs)

  • Perform Image Classification with Convolutional Neural Networks

  • Image Recognition

  • Recurrent Neural Networks (RNNs)

  • Transfer Learning

  • Create Generative Adversarial Networks (GANs) with TensorFlow

  • Autoencoders

  • Introduction to Natural Language Processing

  • Data Analysis with Numpy, Pandas and Data Visualization with Matplotlib

Installation and Colab

1
Google Colab Introduction
2
Anaconda Installation
3
Jupyter Notebook

Tensorflow Introduction

1
Tensorflow Introduction

https://www.goeduhub.com/10592/what-is-tensorflow-and-how-to-install-tensorflow-2

2
Eager Execution

https://www.goeduhub.com/10600/tensorflow-using-eager-execution

Core concepts of Neural Network

1
Describe Artificial Intelligence and Machine Learning and Deep Learning

https://www.goeduhub.com/10370/machine-learning-vs-deep-learning

2
Introduction to Neural Network

Reference Notes - https://www.goeduhub.com/10312/what-neural-networks-explain-neural-network-architecture

3
Types of Classification Problem
4
Activation Function part 1

Reference Notes- https://www.goeduhub.com/10050/activation-functions-in-neural-network

5
Activation Function part 2

Reference Notes- https://www.goeduhub.com/10050/activation-functions-in-neural-network

6
Forward Propogation

https://www.goeduhub.com/10374/how-do-neural-network-work-in-forward-propagation

7
Back Propogation

https://www.goeduhub.com/10376/how-back-propagation-works-in-neural-network

8
Chain Rule

https://www.goeduhub.com/10454/what-is-chain-rule-of-differentiation-in-back-propagation

9
Gradient Descent

https://www.goeduhub.com/10105/describe-gradient-descents-and-its-types

Keras Implementation on CIFAR 10 and MNIST Datasets

1
What is Keras

https://www.goeduhub.com/2274/what-is-keras?show=2274#q2274

2
CIFAR 10
3
Fashion MNIST Part 1
4
Fashion MNIST Part 2
5
Fashion MNIST Part 3

CNN Neural Network

1
What is CNN
2
Working of CNN
3
MNIST digit classification
4
cat dog classification

colab link- https://colab.research.google.com/drive/1ReYP1y9kcTTMcWMM-fIowjnigS5rMIuR?usp=sharing

5
cat dog classification 2
6
facial expression recognition 1
7
facial expression recognition 2

colab - https://colab.research.google.com/drive/1YKWlXfElTiimqpuUcqA4wrIHH4QDqQ-v?usp=sharing

8
leaf diseases 1

Reference Notes - https://www.goeduhub.com/10519/project-leaf-disease-detection-and-recognition-using-cnn?show=10519#q10519

9
leaf diseases 2

RNN

1
RNN INTRODUCTION

https://www.goeduhub.com/10039/what-is-rnn-recurrent-neural-network

2
LSTM

https://www.goeduhub.com/10309/lstm-network-in-rnn?show=10309#q10309

3
Text classification
4
practical approach to word embedding
5
Bidirectional neural network

https://www.goeduhub.com/10742/what-is-bidirectional-recurrent-neural-network

Autoencoders

1
Introduction to Autoencoders
2
implementation of autoencoder

Colab file link- https://colab.research.google.com/drive/1JTmux8dSx60_GXOUg1re9UCbnJVAzGpx?usp=sharing


Transfer Learning

1
CNN Transfer Learning
2
Data Augmentation

GAN

1
What is GANs

Reference Notes - https://www.goeduhub.com/11418/generative-adversarial-networks-generator-discriminator?show=11418#q11418

https://www.goeduhub.com/6049/instructor-training-artificial-intelligence-learning-learning

2
DCGAN INTRODUCTION
3
DCGAN Project

Reference Notes - https://www.goeduhub.com/10614/generate-convolutional-generative-adversarial-networks?show=10614#q10614

https://www.goeduhub.com/10616/generate-convolutional-generative-adversarial-networks?show=10617#a10617

Code Colab - https://colab.research.google.com/drive/1NdYHHwXuVLBMinLTbWgmLUJd737QjDd2?usp=sharing

https://www.goeduhub.com/6049/instructor-training-artificial-intelligence-learning-learning

Generative Deep Learning

1
Neural Style Transfer
2
Neural Style Transfer Implementation part 1

code colab-https://colab.research.google.com/drive/1LGW57jra6KP7xCIcOJkWx8T0xfggHmRc?usp=sharing

3
Neural Style Transfer Implementation part 2

Crash course on Machine Learning

1
Concept of Machine Learning
2
What is Supervised Machine Learning and Linear Regression Algorithm
3
What is UnSupervised Machine Learning

Crash Course on Data Science Libraries

1
Python for Data Analysis- Numpy
2
Pandas Series
3
Pandas DataFrames
4
Grouping and Filtering
5
Slicing and Sorting
6
Pandas Missing Values
7
Pandas Aggregation Functions
8
Matplotlib Introduction
9
Matplotlib Bar Graphs
10
Matplotlib Histogram
11
Matplotlib Scatter Plot
12
Matplotlib Area Plot
13
Matplotlib Pie Chart
14
Matplotlib Subplots
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Tensorflow 2 & Keras:Deep Learning & Artificial Intelligence
Category:
IT & Software
Teacher
Daniel W
Price:
$168.98 $129
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