Learn · Artificial Intelligence and Machine Learning in Materials Engineering
Lecture 45 of 78Week 8
Lec. 24 (Part 1): Machine Learning Algorithms - XVII
Prof. Krishanu Biswas · IIT Kanpur
Credits and licence
- From
- Artificial Intelligence and Machine Learning in Materials Engineering, IIT Kanpur (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- Lecture 01 (Part I)- Introduction to the Course - Part 1
- Lecture 01 (Part II) - Introduction to the Course - Part 2
- Lecture 02 (Part I) - Introduction to AI-Part 1
- Lecture 02 (Part II)- Introduction to AI-Part 2
- Lecture 03 - Basics of Materials Science - I
- Lecture 4 - Basics of Materials Science - II
- Lecture 5(Part-I) - Basics of Materials Science -III
- Lecture 5 (Part-II) - Basics of Materials Science -IV
- Lecture 6 (Part - I): Basics of Materials Science - V
- Lecture 6 (Part - II): Basics of Materials Science - VI
- Lecture 7 (Part - I): Basics of Materials Science - VII
- Lecture 7 (Part - II): Basics of Materials Science - VIII
- Lecture 8 (Part - I): Basics of Materials Science - IX
- Lecture 8 (Part - II): Basics of Materials Science - X
- Lecture 9 (Part - I): Basics of Materials Science - XI
- Lecture 9 (Part - II): Basics of Materials Science - XII
- Lecture 10 (Part I): Basics of Materials Science - XIII
- Lecture 10 (Part II): Basics of Materials Science - XIV
- Lecture 11 (Part I): Basics of Materials Science - XV
- Lecture 11 (Part II): Basics of Materials science - XVI
- Lecture 12 (Part I): Basics of Materials Science - XVII
- Lecture 12 (Part II): Basics of Materials Science - XVIII
- Lecture 13 (Part I): Basics of materials Science - XIX
- Lecture 13 (PART II): Basics of Materials Science - XX
- Lecture 14 (Part 1): Basics of Materials Science XXI
- Lecture 14 (Part II): Basics of Materials Science - XXII
- Lecture 15 (Part I): Machine Learning Algorithms
- Lecture 15 (Part II): Machine Learning Algorithms
- Lecture 16 (Part I) : Machine Learning Algorithm -I
- Lecture 16 (Part II) : Machine Learning Algorithm-II
- Lecture 17 (Part I): Machine Learning Algorithms -III
- Lecture 17 (Part II): Machine Learning Algorithms -IV
- Lecture 18 (Part I) : Machine Learning Algorithms -V
- Lecture 18 (Part II): Machine Learning Algorithms - VI
- Lec. 19 (Part 1): Machine Learning Algorithms - VII
- Lec. 19 (Part 2): Machine Learning Algorithms - VIII
- Lec. 20 (Part 1): Machine Learning Algorithms - IX
- Lec. 20 (Part 2): Machine Learning Algorithms - X
- Lec. 21 (Part 1): Machine Learning Algorithms - XI
- Lec. 21 (Part 2): Machine Learning Algorithms - XII
- Lec. 22 (Part 1): Machine Learning Algorithms - XIII
- Lec. 22 (Part 2): Machine Learning Algorithms - XIV
- Lec. 23 (Part 1): Machine Learning Algorithms - XV
- Lec. 23 (Part 2): Machine Learning Algorithms - XVI
- Lec. 24 (Part 1): Machine Learning Algorithms - XVII
- Lec. 24 (Part 2): Machine Learning Algorithms - XVIII
- Lec. 25 (Part 1): Deep learning methods - I
- Lec. 25 (Part 2): Deep learning methods- II
- Lec. 26 (Part 1): Deep Learning methods- III
- Lec. 26 (Part 2): Deep Learning methods- IV
- Lec. 27 (Part 1): Deep Learning methods- V
- Lec. 27 (Part 2): Deep Learning methods- VI
- Lec. 28 (Part 1): Deep Learning Methods- VII
- Lec. 28 (Part 2): Deep Learning Methods- VIII
- Lec. 29 (Part 1): Application of ML and AI in Materials Sciences- I
- Lec. 29 (Part 2): Application of ML and AI in Materials Sciences- II
- Lec. 30 (Part 1): Application of ML and AI in Materials Sciences- III
- Lec. 30 (Part 2): Application of ML and AI in Materials Sciences- IV
- Lec. 31 (Part 1): Application of ML and AI in Materials Sciences- V
- Lec. 31 (Part 2): Application of ML and AI in Materials Sciences- VI
- Lec. 32 (Part I): Molecular Dynamics Simulation - I
- Lec. 32 (Part II): Molecular Dynamics Simulation - II
- Lec. 33 (Part I): Density Functional Theory (DFT) - I
- Lec. 33 (Part II): Density Functional Theory (DFT) - II
- Lec. 34 (Part 1): Advanced Deep Learnig - I
- Lec. 34 (Part 2): Advanced Deep Learning - II
- Lec. 35 (Part 1): Advanced Deep Learning - III
- Lec. 35 (Part 2): Advanced Deep Learning - IV
- Lec. 36 (Part 1): Data Processing and Error Analyses - I
- Lec. 36 (Part 2): Data Processing and Error Analyses - II
- Lec. 37 (Part I): Material Informatics- I
- Lec. 37 (Part II): Material Informatics- II
- Lec. 38 (Part I): Materials Knowledge & Materials Data Science, Material Informatics- I
- Lec. 38 (Part II): Materials Knowledge & Materials Data Science, Material Informatics- II
- Lec. 39 (Part I): Materials knowledge & materials data science, Material informatics- III
- Lec. 39 (Part II): Materials Knowledge & Materials Data Science, Material Informatics- IV
- Lec. 40 (Part I): Materials Knowledge & Materials Data Science, Material Informatics- V
- Lec. 40 (Part II): Conclusion