Bitcoin predictor model can help to predict the bitcoin prices based on the time series data. The model is trained with 4 years of data to identify patterns and trends. Tensorflow’s LSTM deep learning model has been used to create the model.
Model Package - Fulfilled on Amazon SageMaker
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The Hello Forex application provides a browser-based interface to explore and download over 105 million currency conversion data points for 18 different currency pairs: AUDJPY, AUDUSD, CHFJPY, EURCAD, EURCHF, EURGBP, EURJPY, EURUSD, GBPCHF, GBPJPY, GBPUSD, NZDJPY, NZDUSD, USDCAD, USDCHF, USDJPY,...
Linux/Unix, Ubuntu 16.04 - 64-bit Amazon Machine Image (AMI)
Seeq is an advanced analytics solution for process manufacturers that enables organizations to rapidly investigate and share insights from data in Amazon Web Services, as well as contextual data in manufacturing and business systems. Seeq's extensive support for time series data and its inherent...
Vanillatech Labs is a neuro-bio inspired generic deep learning algorithm that works as simple as an intelligence test. It automatically detects patterns in time series and allows you to make predictions. While other ML approaches become more and more complex we wanted to build a model that is...
Datapred streamlines everything that is specific about time series modeling at every stage of the ML pipeline, ensuring significant performance gains and a 10x faster garage-to-factory cycle. Features include: Preprocessing - Prevention of future leakage (automatic data alignment) - Target...
Linux/Unix, Ubuntu 18.04 - 64-bit Amazon Machine Image (AMI)
Operating Expenses Forecasting generates 30 weeks of forward forecast of the operating expenses using historical data. This will help businesses predict and manage their operating expenses more effectively through better working capital management and improved planning for resource allocation. The...
Model Package - Fulfilled on Amazon SageMaker
Energy Consumption Forecasting generates 30 months of forward forecast of the consumption using historical data. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and better results due to its ensemble learning approach. This solution...
Model Package - Fulfilled on Amazon SageMaker
Mphasis time series ticket forecasting helps businesses predict the number of tickets of a specific type based on historic data. This will help businesses assess the level of automation as well as human intervention required to resolve the issues and plan accordingly. It uses ensemble ML algorithms...
Model Package - Fulfilled on Amazon SageMaker
Data evolves over time, causing a change in the distributions and interpretation of data and a corresponding degradation in model performance. The Drift Detector uses an incremental learning method, in which each incoming instance retrains the model. The solution detects drifts in the model output,...
Model Package - Fulfilled on Amazon SageMaker
Retail Sales Forecasting generates 30 months of forward forecast of retail sales using historical data. This solution helps retailers to predict future sales and thereby optimize their inventory, logistics, warehouse management, production planning, personnel allocation, etc. It uses ensemble ML...
Model Package - Fulfilled on Amazon SageMaker
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