AI, a term of which it's true definition is still debated on, but most of us still have a hope, fear or opinion about. Some people can't wait for what the future of it will bring, some just hope it won't be as scary as they envision it to become. This night was all about lifting a corner of the veil covering it by our professional Girl Coders. This slideshare contains the slides of: - Girl Code intro by Ineke Scheffers - Key note: Demystifying AI - Robots are coming by Flavia Sequeira - Your first AI: demo of a beginner's TensorFlow project by Esther van der Giessen

1. @GirlCodeNL
/GirlCodeNL

2. @GirlCodeNL
/GirlCodeNL
We are Girl Code
katja
kristin
ineke@afkatja
@kriepy
@FYIneke

3. @GirlCodeNL
/GirlCodeNL
So, AI...
“This technology will enhance us. So instead of
artificial intelligence, I think we'll augment
our intelligence”
- Ginni Rometty
“The development of full artificial intelligence
could spell the end of the human race”
- Stephen Hawking

4. @GirlCodeNL
/GirlCodeNL
Key note: Demystifying AI - Robots are coming
- Flavia Sequeira
Break
Your first AI: demo of a beginner's TensorFlow project
- Esther van der Giessen
Panel discussion
- Flavia Sequeira, Bidisha Agarwal,
Jana Brummel and Esther van der Giessen
Snacks and drinks!
Program

5. @ernstnaezer @flaviasomething
Robots are
coming!
@flaviasomething

7. What is AI?

8. What is AI > The Future

9. What is AI > Part of Everyday Life

11. What is AI > Science Fiction

13. General AI

17. Narrow AI

18. smart algorithms, machine learning, deep
learning, neural networks, regression,
supervised learning, unsupervised learning

19. natural language processing, computer vision,
face recognition, character recognition,
intelligent assistants, fraud detection, predictions

23. "AI is whatever hasn't been done yet."
- Tesler’s Theorem

24. What are possible applications?

26. Why now?

28. Deep Learning

29. Nvidia

30. Deep Networks

32. What’s under the hood?

33. Deductive > Inductive

34. Traditional Programming v.s. Machine Learning
computer
dataprogram
output

35. if (outlook = ☀) AND (temperature = low) AND (windy = no)
return “play”
else if (outlook = ☀) AND (temperature = high) AND (windy = no)
return “no play”
else if (outlook = ☀) AND (temperature = high) AND (windy = no)
return “no play”
else if (outlook = ☁) AND (temperature = low) AND (windy = no)
return “play”

36. Traditional Programming v.s. Machine Learning
computer
dataprogram
output
computer
dataoutput
program

37. collect select train test

38. What to watch out for?

39. fairness
BIAS

40. is it real?

41. is it real?

42. coverage

43. responsibility, explainability, auditability

44. Example cases

51. take X & add electricity

52. take X & add AI

53. @ernstnaezer @flaviasomething
Robots are
already here
@flaviasomething

54. THANK YOU

55. Your first AI: demo of a beginner's
TensorFlow project
Esther van der Giessen

56. About me
- B in Neuroscience
- Programming courses in last year (3 years ago)
- M in Artificial Intelligence
- Developer in FinTech company

57. First AI
- My First AI:
- Kaggle competition: predict survivors titanic
-
- Your first AI:
- Tensorflow
- Image recognition

58. Machine Learning
1. Dataset
2. Train model
3. Make prediction
88% raspberry

59. Step 1: install TensorFlow
- Go to: www.tensorflow.org/install/
- Go to guide of your operating system
- Check Python requirements → install python
https://www.python.org/downloads/
- Mac: Python 2.7 or 3.3+, 64 bit
- Windows: Python 3.5 or 3.6, 64 bit
- Use Pip to install TensorFlow (CPU version)

60. TensorFlow → Tutorials → Image Recognition
1. Download document
2. Open terminal
3. Go to folder with file
4. Run python file
5. Output
https://www.tensorflow.org/tutorials/image_recognition

61. Suggestions other first projects
- Tensorflow:
- Chatbot, speech recognition
- Fancier image recognition:
https://pythonprogramming.net/introduction-use-tensorflow-object-detection-api-tutorial/
- Datasets/competitions: www.kaggle.com
- Youtube: Siraj Raval