I have just started a course on artificial intelligence. The course opens with an assignment where the student must implement the minimax algorithm and variations on the algorithm in order to play a reversi-like game. The game is called isolation and is very similiar to tron. Players make a move, rendering the previously occupied square unusuable for the duration of the game. The objective of the game is to prevent the opponent from making anymore moves.
I just took a course on software analysis. The course was created by Prof. Mayur Naik and the course website is here. Course notes are available here. Below I present some facts I learned. The syllabus lists a bunch of tools used for software analysis. I am going to discuss randoop type systems dynamic symbolic execution Randoop Here is some background reading material on the randoop tool. Some employees at Microsoft Research worked on a technique for test generation called “feedback-directed random test generation”.
This has been an exciting summer. Machine learning has been quite the buzzword in the past few years. Now that I have learned more about the methods, I know for a fact that they hype is a bunch of crap. Garbage in garbage out. If an organization has bad data, machine learning will garner terrible insights from that data. some ML techniques: LinearRegression DecsionTree RandomTree BagLearner k-Means QLearning some domain knowledge on markets
Hoo-wee. Up to assignment 4 for the Machine Learning for Trading course. A quick summary of the previous three. Martingale betting strategy formulation Spin the wheel, win at roulette. Evaluate betting strategy Basic probability (n out of m slots) Optimize a portfolio to maximize sharpe return Useful methods for evaluating portfolios of securities Implement and assess decision trees and boostrap aggregating methods machine learning basics decision trees can double as classifier and regressor
I am currently taking a course on machine learning and trading. The syllabus can be found here. The course serves as an introduction to machine learning methods and how to apply them to finance. Topics to discuss in course: stock market basics pandas k nearest neighbor learning decision trees reinforcement learning
Something I should have done when I started grad school is maintain a bibliography. Throughout college and high school I used EasyBib or some other simple software to generate citations. Google Scholar will also generate citations in multiple formats, but accuracy varies. There are software available to make data entry easier. I tried JabRef, which is a JVM based citation manager. JabRef compiles bibtex files. The interface is reasonably designed. Then I tried Zotero, which features web browser integrations.