Author:Moises Sanchez AdamePublications |
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| EasyChair Preprint 15191 | EasyChair Preprint 15191 |
KeyphrasesCIFAR-100, city yellow taxi dataset, Coefficient of determination, CUDA programming, cudf, cuML, CuPy, DASK Framework, data parallel model, Data Science Infrastructure, deep learning, Description and Analysis, distributed data parallel training platform, distributed data processing, distributed training pipeline, Elastic Net, Emerging Technology, execution time, fare distribution analysis, fare predictions, GPU (Graphics Processing Unit), GPU(Graphics Processing Unit), High Performance Computing, image classification, Karp-Flatt Metric, machine learning, Machine Learning Optimization, Mathematical simulations2, mean squared, MobileNet-V3-Large, nvidia multi gpus, parallel computing, parallel efficiency, parallel programming, parallelism, PyTorch Integration, RandomForest, RAPIDS-24.06, rapids integration figure, Scalability2, Smart City Development, speedup analysis, Taxi fare prediction, transportation analytics, trip fare prediction, XGBoost. |
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