#Fantastic4
Organized By
ESEN Android Club
Hello!
I am Rebai Ahmed
I am here because I love to give presentations && I love Tensorflow
Check out my portfolio rebai.ahmed.github.io
2
Plan
3
➢ Introduction
➢ What is Tensorflow ?
➢ Why Tensorflow ?
➢ Cool Projects with Tensorflow
➢ Conclusion
Quick Questions
➢ How many people have heard about Deep Learning | Machine learning |
tensorflow ?
➢ How many people know about Deep Learning | Machine learning | tensorflow
?
➢ How many people are using Deep Learning | Machine learning | tensorflow ?
4
1. Introduction
Artificial Intelligence, deep learning, machine learning — 
whatever you’re doing if you don’t understand it — learn it.
Because otherwise you’re going to be a dinosaur within 3 years.
Mark Cuban
Introduction : What is Machine learning ?
★ Subfield of Artificial Intelligence (AI) gives "computers the ability to
learn without being explicitly programmed"
★ Machine learning is preferred approach to :
➢ Weather prediction
➢ Recommendation systems
➢ Spam Filtering
7
Introduction : What is Machine learning (2) ?
8
Introduction : What is Deep Learning ?
Deep Learning is a subfield of Machine
learning concerned with algorithms inspired by
the structure and the function of the brain called
artificial neural network.
9
Introduction : What is Deep Learning ?
➢ Our brain has lots of neurons connected
together and the strength of
the connections between neurons
represents long term knowledge.
Neurons in the brain
10
Introduction : What is Deep Learning ?
Neural Network (Deep Learning)
11
Introduction : Deep learning Why Now ?
12
Introduction : Deep learning Why Now ?
➢ Big DATA
➢ big processing power
➢ robust neural networks
13
Tools
2. What is TensorFlow ?
● TensorFlow is an open-source library for Deep Learning and Machine learning
● Developed by the Google Brain team and released in November 2015
● TensorFlow is mainly used for: Classification, Perception, Understanding,
Discovering, Prediction and Creation
14
2. What is TensorFlow ?
TensorFlow = Tensor + Flow = Data +
Flow
15
2. But What is Tensor ?
An n-dimensional array :
➢ 0-d tensor: scalar (number)
➢ 1-d tensor: vector
➢ 2-d tensor: matrix
➢ and so on
16
2. But What is Tensor Flow?
Data Flow Graphs
➢ Dataflow is a common programming model for
parallel computing.
➢ TensorFlow uses a dataflow graph to
represent your computation
17
2. What are the benefits of using graphs ?
➢ Parallelism. ( it is easy for the system to identify operations that can
execute in parallel )
➢ Distributed execution ( it is possible for TensorFlow to partition your program
across multiple devices CPUs, GPUs, and TPUs)
➢ Compilation (generate faster code)
➢ Portability (You can build a dataflow graph in Python, store it in a Saved
Model, and restore it in a C++ program )
18
More in Tensorflow:
Machine learning in Javascript
19
More in Tensorflow:
➢ It possible to add machine learning capabilities to any web application
➢ You can use the APIs to build and train models right in the browser or in
your Node.js server application
➢ You can use TensorFlow.js to run existing models in your JavaScript
environment.
20
21
Demo1 Tensorflow
Code Demo
3. Why Tensorflow ?
22
23
Why TensorFlow : Runs Everywhere
Runs on desktop and mobile devices such as
● Linux
● macOS
● iOS
● Android
● Raspberry pi
● And Windows
24
Why TensorFlow : Flexibility
● Python API offers flexibility to create all sorts of
computations(Including any neural network
architecture we can think of)
● Includes highly efficient C++ implementations of
many ML operations
25
Why TensorFlow: Parallel Computation
TensorFlow supports distributed computing
26
Why TensorFlow : Large community
● One the the most popular open source projects
on GitHub
● It has a dedicated team of passionate and
helpful developers
● Growing community contributing to improve it
27
Why TensorFlow :Google products
● It powers many of Google’s large-scale services, such as
○ Google Cloud Speech
○ Google Photos and
○ Google Search
28
Why TensorFlow : Big Companies using
Tensorflow
● Google
● OpenAI
● DeepMind
● Uber
● eBay
● DropBox
● A bunch of startups
Cool Projects with Tensorflow
Project1 : Image Classification
29
Cool Projects with Tensorflow
Project 2: Object Detection
30
Cool Projects with Tensorflow
Project 3: Speech recognition
31
Cool Projects with Tensorflow
Project 4: Deep learning driven jazz generation
32
Cool Projects with Tensorflow
Project 5: Restore colors in B&W photos and videos
33
Cool Projects with Tensorflow
Project 6: Transferring style from famous paintings
34
5. Conclusion
There are numerous and amazing things that people
have done using machine learning, some of which include
applications relating to health care, recommendation engines
for movies, music, personalized ads, and social media
sentiment mining to name a few.
With these advancements in machine learning and artificial
intelligence that seem mind-boggling, TensorFlow is tool that
is helping to achieve these goals
35
Ressources
36
➢ TensorFlow tutorials
➢ quora.com/topic/TensorFlow-software-library
➢ Machine learning crash course
➢ Your first TensorFlow programming with Jupyter
➢ TensorFlow Dev-Summit 2018
Question ?
37
What is a tensor in TensorFlow?
➢ 1) : a generalization of vectors and Matrices to potentially higher
dimensions ?
➢ 2) : common programming model for parallel computing ?
38
Thanks!
Any questions?

You can find me at rebai.ahmed@outlook.com

Tensorflow presentation

  • 1.
  • 2.
    Hello! I am RebaiAhmed I am here because I love to give presentations && I love Tensorflow Check out my portfolio rebai.ahmed.github.io 2
  • 3.
    Plan 3 ➢ Introduction ➢ Whatis Tensorflow ? ➢ Why Tensorflow ? ➢ Cool Projects with Tensorflow ➢ Conclusion
  • 4.
    Quick Questions ➢ Howmany people have heard about Deep Learning | Machine learning | tensorflow ? ➢ How many people know about Deep Learning | Machine learning | tensorflow ? ➢ How many people are using Deep Learning | Machine learning | tensorflow ? 4
  • 5.
    1. Introduction Artificial Intelligence,deep learning, machine learning —  whatever you’re doing if you don’t understand it — learn it. Because otherwise you’re going to be a dinosaur within 3 years. Mark Cuban
  • 6.
    Introduction : Whatis Machine learning ?
  • 7.
    ★ Subfield ofArtificial Intelligence (AI) gives "computers the ability to learn without being explicitly programmed" ★ Machine learning is preferred approach to : ➢ Weather prediction ➢ Recommendation systems ➢ Spam Filtering 7 Introduction : What is Machine learning (2) ?
  • 8.
    8 Introduction : Whatis Deep Learning ? Deep Learning is a subfield of Machine learning concerned with algorithms inspired by the structure and the function of the brain called artificial neural network.
  • 9.
    9 Introduction : Whatis Deep Learning ? ➢ Our brain has lots of neurons connected together and the strength of the connections between neurons represents long term knowledge. Neurons in the brain
  • 10.
    10 Introduction : Whatis Deep Learning ? Neural Network (Deep Learning)
  • 11.
    11 Introduction : Deeplearning Why Now ?
  • 12.
    12 Introduction : Deeplearning Why Now ? ➢ Big DATA ➢ big processing power ➢ robust neural networks
  • 13.
  • 14.
    2. What isTensorFlow ? ● TensorFlow is an open-source library for Deep Learning and Machine learning ● Developed by the Google Brain team and released in November 2015 ● TensorFlow is mainly used for: Classification, Perception, Understanding, Discovering, Prediction and Creation 14
  • 15.
    2. What isTensorFlow ? TensorFlow = Tensor + Flow = Data + Flow 15
  • 16.
    2. But Whatis Tensor ? An n-dimensional array : ➢ 0-d tensor: scalar (number) ➢ 1-d tensor: vector ➢ 2-d tensor: matrix ➢ and so on 16
  • 17.
    2. But Whatis Tensor Flow? Data Flow Graphs ➢ Dataflow is a common programming model for parallel computing. ➢ TensorFlow uses a dataflow graph to represent your computation 17
  • 18.
    2. What arethe benefits of using graphs ? ➢ Parallelism. ( it is easy for the system to identify operations that can execute in parallel ) ➢ Distributed execution ( it is possible for TensorFlow to partition your program across multiple devices CPUs, GPUs, and TPUs) ➢ Compilation (generate faster code) ➢ Portability (You can build a dataflow graph in Python, store it in a Saved Model, and restore it in a C++ program ) 18
  • 19.
    More in Tensorflow: Machinelearning in Javascript 19
  • 20.
    More in Tensorflow: ➢It possible to add machine learning capabilities to any web application ➢ You can use the APIs to build and train models right in the browser or in your Node.js server application ➢ You can use TensorFlow.js to run existing models in your JavaScript environment. 20
  • 21.
  • 22.
  • 23.
    23 Why TensorFlow :Runs Everywhere Runs on desktop and mobile devices such as ● Linux ● macOS ● iOS ● Android ● Raspberry pi ● And Windows
  • 24.
    24 Why TensorFlow :Flexibility ● Python API offers flexibility to create all sorts of computations(Including any neural network architecture we can think of) ● Includes highly efficient C++ implementations of many ML operations
  • 25.
    25 Why TensorFlow: ParallelComputation TensorFlow supports distributed computing
  • 26.
    26 Why TensorFlow :Large community ● One the the most popular open source projects on GitHub ● It has a dedicated team of passionate and helpful developers ● Growing community contributing to improve it
  • 27.
    27 Why TensorFlow :Googleproducts ● It powers many of Google’s large-scale services, such as ○ Google Cloud Speech ○ Google Photos and ○ Google Search
  • 28.
    28 Why TensorFlow :Big Companies using Tensorflow ● Google ● OpenAI ● DeepMind ● Uber ● eBay ● DropBox ● A bunch of startups
  • 29.
    Cool Projects withTensorflow Project1 : Image Classification 29
  • 30.
    Cool Projects withTensorflow Project 2: Object Detection 30
  • 31.
    Cool Projects withTensorflow Project 3: Speech recognition 31
  • 32.
    Cool Projects withTensorflow Project 4: Deep learning driven jazz generation 32
  • 33.
    Cool Projects withTensorflow Project 5: Restore colors in B&W photos and videos 33
  • 34.
    Cool Projects withTensorflow Project 6: Transferring style from famous paintings 34
  • 35.
    5. Conclusion There arenumerous and amazing things that people have done using machine learning, some of which include applications relating to health care, recommendation engines for movies, music, personalized ads, and social media sentiment mining to name a few. With these advancements in machine learning and artificial intelligence that seem mind-boggling, TensorFlow is tool that is helping to achieve these goals 35
  • 36.
    Ressources 36 ➢ TensorFlow tutorials ➢quora.com/topic/TensorFlow-software-library ➢ Machine learning crash course ➢ Your first TensorFlow programming with Jupyter ➢ TensorFlow Dev-Summit 2018
  • 37.
    Question ? 37 What isa tensor in TensorFlow? ➢ 1) : a generalization of vectors and Matrices to potentially higher dimensions ? ➢ 2) : common programming model for parallel computing ?
  • 38.
    38 Thanks! Any questions?  You canfind me at rebai.ahmed@outlook.com