FDP on AI and ML by R. Rajkumar
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Organized by PG Department of Computer Science and Application ISLAMIAH WOMEN’S ARTS AND SCIENCE COLLEGE, VANIYAMBADI Tirupattur District, Tamil Nadu - 635752 One Day Faculty Development Programme On “BUILD YOUR FUTURE IN MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE" Date:23.06.2020 Time: 04.00 PM TO 05.00 PM(IST) -->No Registration fees. -->Feedback form will be shared at the END of the session -->E-Certificate will be provided to all the participants. Registration link https://forms.gle/JmtLZYNTx9uYUokH7 With regards Dr.M.RENU PRINCIPAL Ms.K. PRIYA Head, Department of Computer Science and Application, Islamiah Women's Arts and Science College VANIYAMBADI.
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FDP on AI and ML by R. Rajkumar
- 1. Build your Future in Artificial Intelligence and Machine Learning Mr. R. Rajkumar Assistant Professor Department of Computer Science and Engineering SRM Institute of Science and Technology ISLAMIAH WOMEN’S ARTS AND SCIENCE COLLEGE, VANIYAMBADI Faculty Development Program on Date: 23.06.2020
- 3. Artificial Intelligence Most Intelligence Creatures
- 5. Artificial Intelligence India is among the top five countries globally when it comes to the number of AI-driven startups Many factors are likely to play a large role in shaping the AI scene in 2025 Most products will be using AI by 2025 and many AI-first companies will emerge across sectors
- 6. Artificial Intelligence Every data is useful Faculty / Research Scholar Point of View
- 7. Artificial Intelligence Apply Design thinking to the data Faculty / Research Scholar Point of View
- 8. Artificial Intelligence Create the projects for local problems Faculty / Research Scholar Point of View
- 9. Artificial Intelligence Need to convert the projects to AI Enable Faculty / Research Scholar Point of View
- 10. Artificial Intelligence Need to convert the projects to product Faculty / Research Scholar Point of View
- 11. Artificial Intelligence Create/Convert users for your product Faculty / Research Scholar Point of View
- 16. Get Set Ready Go
- 51. Case Study - 1
- 53. Product name: Cookies “Tasting too good” Rated 4 Stars “Not Bad” Rated 2 Stars
- 54. Product name: Cookies Positive Review : Class 1 Negative Review: Class 2 Binary Classification 1. n Number of Reviews with Class Labels 2. +ve reviews with stars 3. -ve reviews with stars 4. Model has been trained 5. x>= 3 : +ve ; x<=2 : -ve;
- 55. Product name: Cookies Positive Review : Class 1 Negative Review: Class 2 Binary Classification 1. n Number of Reviews with Class Labels 2. +ve reviews with stars 3. -ve reviews with stars 4. Model has been trained 5. x>= 3 : +ve ; x<=2 : -ve;
- 56. Product name: Cookies Bitter taste (0) : Class 1 Sweet taste (1) : Class 2 Salty taste (2) : Class 3 No taste (3) : Class 4 Multi – Class Classification 1. n Number of Reviews with Class Labels 2. reviews with stars 3. Model has been trained 4. n+1 Classes [ (n+1)> 2 ]
- 57. Product name: Cookies Bitter taste (0) : Class 1 Sweet taste (1) : Class 2 Salty taste (2) : Class 3 No taste (3) : Class 4 Multi – Class Classification 1. n Number of Reviews with Class Labels 2. reviews with stars 3. Model has been trained 4. n+1 Classes [ (n+1)> 2 ] English : Multi Means more than 1 Machine Learning: Multi means more than 2
- 59. Case Study - 2
- 62. Clustering using Machine Learning
- 64. Artificial Intelligence Most Intelligence Creatures
- 65. Q & A
- 66. Contact R. Rajkumar Faculty of CSE SRM IST – Chennai +91 9894808403 rajkumar03r@gmail.com