Playing with the Genetics of Python
“Machines are as good as their programmer itself”. Knowledge of Genetic algorithms can help us solve various problems that a typical computer would take years to solve.
These Genetic Algorithms (GAs) are a type of optimization algorithms which combine survival of the fittest and a simplified version of Genetic Process involving selection, mutation and cross-overs to solve NP-hard problems within restricted computational space and time.
This talk will cover the fundamentals and need of Genetic Algorithms. We will solve interesting problems and riddles in Python using Genetic Package. Talk will cover intricate details of how Genetic algorithms are used and being researched by organisations like NASA to solve real world problems.
We will look at:
1. Intro to Genetic Algorithms
2. Rise of Genetic Algorithms and Darwin’s Evolutionary Model
3. Solving riddles using Genetic Algorithms in Python
4. Application of Genetic Algorithms in Machine Learning
5. Latest developments and Research in Genetic Algorithms
6. Python packages to implement Genetic Algorithms
7. Use cases and Analysis
I’m a computer science, undergrad, having a research aptitude and great interest in Machine Learning. I’ve been research intern at IIT, Ropar as well as worked with professor at IIM Lucknow on Data Analytics.I have mentored my juniors at Technical Dept of Ecell MSIT on these topics and also contributed to python community of Stanford Scholar Initiative that worked on Python and various Research papers in a collaborative way. I’ve done 6 internships about 10 MOOCs and contributed to 4 research papers, currently working with a post-doc professor from UT Austin in Machine Learning.