🌟 Scott Miner's GitHub portfolio showcasing personal projects, coding skills, and expertise in Software Development/Data Analytics/AI/ML. Get in touch for collaboration!
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Updated
Mar 6, 2024
🌟 Scott Miner's GitHub portfolio showcasing personal projects, coding skills, and expertise in Software Development/Data Analytics/AI/ML. Get in touch for collaboration!
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.
Persian text generation using GRU model and persian wikipedia dataset
Pytorch Implementation of DeepLog.
Four digit SVHN (Street View House Number) sequence prediction with CNN using Keras with TensorFlow backend
Predict next number in a sequence using a simple ANN. Modularized code with classes for data preparation, neural network architecture, and training.
Opportunistic planning model to generate action sequence predictions for human behavior in everyday activities
A LSTM model to predict the next Fibonacci number.
Transformer-based Implementation of DeepLog.
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.
An Implementation of the Context Tree Weighting (CTW) Sequence Prediction Algorithm
Prediction of the binding specificity of transcription factors using support vector regression
An attempt to implement machine learning techniques for sequence predictions
Comparison of Sequence Prediction Algorithms on a Structured Prediction Problem
LSTM network using Keras for sequence prediction
Project using Compact Prediction Tree Algorithm. Based on the paper "Compact Prediction Tree : A lossless model for accurate sequence prediction"
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.
biLSTM model with the attention mechanism. Example of prediction/inferencing included.
Temporal Convolutional Network for Sequence Modelling
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