Invited as Resource Person on workshop named "Advanced Machine Learning with Python" held at SDMCET, Dharwad. The whole talk was structured into two sessions.One for Artificial Intelligence and another for Machine Learning. The Presentation touched upon techniques and classifications involved in Machine Learning, WorkFlow for building an AI model. Finally, participants explored how to work on TensorFlow using katacoda platform.

1. Artificial Intelligence
Pravin Hanchinal
pravinhanchinal.com

2. Disclaimer
All the images are used for educational purposes only.
All the images in the presentation are obtained from
internet with “free to use license” search. Some of them
are from free stock photos like pexels website.
If you are owner of any images with copyright.
Kindly report. Will remove the images with all respect to
your creative work.

3. About Me
Educator,
Entrepreneur,
Innovator,
Cloud, Big Data, IoT, AI Evangelist
pravinhanchinal.com

5. What is AI?
The science of intelligent programs

6. The Brain of AI | Neural Networks

7. Let’s See in Action: http://playground.tensorflow.org/

8. Why Now?

9. ‘Cos People are Stupid and Lazy

10. Smart Door, Still Stupid!

11. Why need Smart Cars...

14. Image source:
https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-lea
rning-ai/

15. AL vs ML vs DL
Artificial Intelligence
— Human Intelligence Exhibited by Machines
Machine Learning
— An Approach to Achieve Artificial Intelligence
Deep Learning
— A Technique for Implementing Machine Learning

16. What AI Deals with?

17. Why AI Important?
1. Reasoning:
the ability to solve problems
2. Knowledge:
the ability to represent knowledge about the world
3. Planning:
the ability to set and achieve goals
4. Communication:
the ability to understand written and spoken language.
5. Perception:
the ability to deduce things from images, sounds, etc

18. What We Need for AI?
Resources
Tools
Information

19. What We Have?
Resources
Enough Computing Power | Cheap Hardware
Human Brains | Build AI Models
Tools
Cloud
Open Source Tools
Information
Data

20. Challenges in AI
Building Trust
AI Human Interface
Investment
Software Malfunction
Can Replace only Certain Tasks
High Expectations

21. PEAS Representation Model
P: Performance measure
E: Environment
A: Actuators
S: Sensors

22. Agriculture
Make AI learn based on our crop references,
to predict pricing
Classification of products using AI
https://www.youtube.com/watch?v=MtQmqaSxszU

23. Working AI: Self Driving Cars
https://youtu.be/tiwVMrTLUWg?t=7m56s

24. You Name it, We can apply it

25. Things Everywhere

26. All our world is made of Things.
Things when connected, form IoT
IoT Won't Work Without Artificial Intelligence!

27. IoT-> AI | How It Works?

29. Machine Learning

31. How Machine Learning work?

32. Types of Machine Learning
❏ Supervised Learning
– Train Me!
❏ Unsupervised Learning
– I am self sufficient in learning
❏ Reinforcement Learning
– My life My rules! (Hit & Trial)

33. Supervised Learning

34. Unsupervised Learning

35. Reinforcement Learning

39. In Future
Drones Monitoring Farms and Harvesting
Law Enforcement:
Self Driving Cars
Text Summarization in Law
Automated RTI
Toilet Doctors | Medical Insurance
Office Less Services: Documents Movement
Automated Citizen Care
Prisoners monitoring

40. In Future
Defence / Military
Behavioural Analysis
Predicting Poverty
Guided Schooling

41. Visioning AI Environment
Birth get registered
Aadhar, Insurance
School suggestion->best friend
College suggestion-> boy friend / girl friend
Job suggestion
Whom to marry
When to have kids
Old age home/Robot suggestion
Instant call to Ambulance
Finally your cemetery based on height

42. Sample Model : X-ROAD
https://www.ria.ee/en/x-road.html

43. AI God
God also knows before you pray

44. Best Research* in IoT/ML
Uses Machine Learning
Synthetic Sensors:
http://www.gierad.com/projects/supersensor/
*read by me

45. What Defines Us?
Creativity and Intelligence

46. The electric light did not come from the
continuous improvement of candles.
-Oren Harani

47. In a Nutshell
Go through presentation again
Explore resources provided
Get Started
Build Small Models and Scale up
Learn From Failures

48. Finally to the tip of iceberg...

49. Enough?
Source: http://www.crackerjackann.net/blog/is-a-lack-of-leads-frustrating-you

50. Thank you
You gave me your time,
the thoughtful gift of all...

51. more presentation at
pravinhanchinal.com/presentations/

52. Stay connected
PravinHanchinal.com
pravinhanchinal@gmail.com
+919740861099

53. References AI
https://nips.cc/
https://blackinai.github.io/
http://wimlworkshop.org/
http://projector.tensorflow.org/
https://openai.com/
https://deeplearnjs.org/index.html
https://research.google.com/teams/brain/
https://gym.openai.com/docs/
https://www.deeplearning.ai/
https://www.datacamp.com/
https://www.youtube.com/watch?v=2ePf9rue1Ao
https://cloud.google.com/tpu/
Playgrounds:
http://playground.tensorflow.org
https://www.katacoda.com/courses/tensorflow/playground
https://www.artificial-intelligence.blog/
https://youtu.be/TRCiS2lnGOk

54. Research References AI
https://www.youtube.com/watch?v=8cmx7V4oIR8
https://www.youtube.com/watch?v=-Y7PLaxXUrs
Self Driving Cars:
https://www.youtube.com/watch?v=URmxzxYlmtg
https://www.youtube.com/watch?v=OlLFK8oSNEM 10:38
http://sustain.stanford.edu/predicting-poverty/
https://interestingengineering.com/this-project-used-drones-to-farm-an-entire-crop-and-its-ready-for-harvesting

55. AI to Play
Cam
https://experiments.withgoogle.com/ai/giorgio-cam/view/
https://www.youtube.com/watch?v=eKeI63VSpto
Draw
https://quickdraw.withgoogle.com/
https://www.youtube.com/watch?time_continue=97&v=X8v1GWzZYJ4
AI Duet
https://experiments.withgoogle.com/ai/ai-duet/view/
https://www.youtube.com/watch?time_continue=126&v=0ZE1bfPtvZo
https://experiments.withgoogle.com/ai/drum-machine/view/