The document provides an overview of TensorFlow, an open-source library for deep learning and machine learning developed by the Google Brain team, which is widely used for various applications including classification and prediction. It explains the benefits of TensorFlow, such as its ability to run on multiple platforms, its flexibility through a Python API, and support for parallel computation, along with examples of cool projects created using TensorFlow. Additionally, the document highlights its popularity and community support in the field of artificial intelligence.

2. Plan
➢ Introduction
➢ What is Tensorflow ?
➢ Why Tensorflow ?
➢ Cool Projects with Tensorflow
➢ Conclusion

3. 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. Introduction : What is Machine
learning ?

5. ★ 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
Introduction : What is Machine learning (2) ?

6. 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.

7. Introduction : What is Deep Learning ?
Neurons in the brain
➢ Our brain has lots of neurons connected
together and the strength of
the connections between neurons
represents long term knowledge.

8. Introduction : What is Deep Learning ?
Neural Network (Deep
Learning)

9. Introduction : Deep learning Why
Now ?
➢ Big DA
T
A
➢ big processing power
➢ robust neural networks

10. Tool
s

11. 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

12. 2. What is TensorFlow ?
TensorFlow = Tensor + Flow = Data + Flow

13. 2. But What isTensor ?
An n-dimensional array :
➢ 0-d tensor: scalar (number)
➢ 1-d tensor: vector
➢ 2-d tensor: matrix
➢ and so on

14. 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

15. 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 )

16. More in Tensorflow:
➢ It possible to add machine learning capabilities to any web application
➢ Y
ou can use the APIs to build and train models right in the browser or in
your Node.js server application
➢ Y
ou can use TensorFlow.js to run existing models in your JavaScript
environment.

17. 3. Why Tensorflow ?

18. Why TensorFlow : Runs Everywhere
Runs on desktop and mobile devices such as
● Linux
● macOS
● iOS
● Android
● Raspberry pi
● And
Windows

19. 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

20. Why TensorFlow: Parallel Computation
TensorFlow supports distributed computing

21. 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

22. Why TensorFlow :Google products
● It powers many of Google’s large-scale services, such as
Google Cloud Speech
Google Photos and
Google Search

23. Why TensorFlow : Big Companies using
Tensorflow
● Google
● OpenAI
● DeepMind
● Uber
● eBay
● DropBox
● A bunch of startups

24. Cool Projects with Tensorflow
Project1 : Image Classification

25. Cool Projects with Tensorflow
Project 2: Object Detection

26. Cool Projects with Tensorflow
Project 3: Speech recognition

27. Cool Projects with Tensorflow
Project 4: Deep learning driven jazz generation

28. Cool Projects with Tensorflow
Project 5: Restore colors in B&W photos and videos

29. Cool Projects with Tensorflow
Project 6: Transferring style from famous paintings

30. Tensorflow
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