Intro to Machine Learning
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slide on an intro to machine learning which I used in CAT event (Hello World), this was mainly designed for beginners who have little knowledge about ML CAT link : https://www.facebook.com/CATReloaded/
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3) The author notes that AI and law is an established research field since the 1980s, and legal applications of AI research like natural language processing are now a wake-up call for the field.
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- The field of AI was established in 1956 at the Dartmouth Conference where researchers proposed using computers to simulate human intelligence.
- Early milestones included programs that played games like checkers and proved mathematical theorems. Research focused on symbolic and knowledge-based approaches.
- In the 1980s, expert systems flourished but funding declined amid doubts about progress, known as an "AI winter." Subsymbolic approaches using neural networks also emerged.
- Modern AI incorporates both symbolic and subsymbolic techniques, with successes in games, robotics, machine learning and other domains. Knowledge representation and common-sense reasoning
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An introduction to AI (artificial intelligence)
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The ppt link is available bellow https://docs.google.com/presentation/d/1-oaO75DEdP259HNrrvh5fbZVOtaiiiffi3luyv0tShw/edit?usp=sharing
you could leave your comments on google slides
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Intro to Machine Learning
- 1. Hi ! Nice to meet you all
- 2. Me?
- 4. Relax and let’s start
- 5. What is AI?
- 6. Relax and let’s start
- 8. Mail spam Not spam Let’s try to make a spam hunter :D
- 9. What the rule that we can use to detect the spam ?
- 10. This is what Google says
- 11. Collect data -> choose model -> train the model -> test -> use
- 12. So ML can be defined as "the field of study that gives computers the ability to learn without being explicitly programmed."
- 13. Machine Learning is super helpful in - Classification problems - Regression problems - Recommendation problems - Clustering problems - And others but I’m super lazy to type more .. “Problems can’t be hard coded “
- 14. Real World Apps
- 15. What do you think of other apps that ML plays a big role at ?
- 16. Machine Learning People Doing researches and Developing new algorithms and models Apply to real world cases and make a useful real world apps Researchers Engineers and Developers
- 17. How to start ? First of all you need basic understanding of programming ● Start with Courses like - MIT introduction to programming using python (edx) - Harvard CS50x (edx) ● Make a github account and start coding and sharing your projects ● Practice on sites like Hackerrank ● Youtube and his friends
- 18. Then for ML material - Stanford Machine Learning Course by Andrew Ng (Coursera) - Machine Learning Specialization by University of Washington (Coursera) - Intro to Machine Learning (Udacity) Also check : ● Google developers ML series ● Kaggle website ● Youtube, it’s super helpful
- 19. Start with open source libraries like
- 20. Questions?
- 21. Demo with iris flowers https://github.com/Mohammed-Ashour/CAT_intro_to_ML/blob/master/machine_learning_session_CAT.ipyn b
- 22. Thanks :)