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A Product Sequence Predictor and Recommender Application made as a part of the Machine Learning Lab Course in the curriculum of B. Tech. Data Science & Engineering at Manipal Institute of Technology.
The repository includes implementations of quaternion networks and new QALE loss function, which calculates the error value based on the difference in angles between the result and the expected value. Procedures for performing the training and evaluation of predicting successive elements of a rotation sequence are also provided.
Rock Paper Scissors using Discrete Markov Chains : The program calculates the probability of the opponent picking one of the three states (R/ P/ S) from choices made by the opponent during the previous games.
🌟 Scott Miner's GitHub portfolio showcasing personal projects, coding skills, and expertise in Software Development/Data Analytics/AI/ML. Get in touch for collaboration!