Services
AI/ML
dotNear helps customers implement Artificial Intelligence & Machine Learning in their business initiatives. This includes enhancements to client’s proprietary AI/ML products and also developing & training new complex machine learning models.
Most commercially successful software applications are beginning to include artificial intelligence – from bots, online sales to algo-traders and other services, where past and general behavior can provide a better experience for each user. Much of the Artificial Intelligence used on the market right now was developed with the help of nearshore AI/ML teams – a natural result of the long-cultivated mathematical skills found in Central and Eastern Europe in general, and very much so in Romania, as well.
dotNear can provide nearshore AI/ML engineers with expertise ranging from data preparation (data scraping, data wrangling, cleansing and pre-processing) to deep learning architectures (deep neural networks, deep belief networks, recurrent neural networks). We can help build, train, deploy and operate Machine Learning models fast.
Languages
- Python, C/C++, R, Java, C#
dotNear helps customers implement Artificial Intelligence & Machine Learning in their business initiatives. This includes enhancements to client’s proprietary AI/ML products and also developing & training new complex machine learning models.
Most commercially successful software applications are beginning to include artificial intelligence – from bots, online sales to algo-traders and other services, where past and general behavior can provide a better experience for each user. Much of the Artificial Intelligence used on the market right now was developed with the help of nearshore AI/ML teams – a natural result of the long-cultivated mathematical skills found in Central and Eastern Europe in general, and very much so in Romania, as well.
dotNear can provide nearshore AI/ML engineers with expertise ranging from data preparation (data scraping, data wrangling, cleansing and pre-processing) to deep learning architectures (deep neural networks, deep belief networks, recurrent neural networks). We can help build, train, deploy and operate Machine Learning models fast.
Languages
- Python, C/C++, R, Java, C#
Libraries and engines
- TensorFlow
- Scikit Learn
- Pytorch
- Keras
- KNIME
Platforms
- Google AI Platform (Unified)
- AWS Machine Learning, Amazon SageMaker
- Microsoft Azure Machine Learning (Azure ML)
Libraries and engines
- TensorFlow
- Scikit Learn
- Pytorch
- Keras
- KNIME
Platforms
- Google AI Platform (Unified)
- AWS Machine Learning, Amazon SageMaker
- Microsoft Azure Machine Learning (Azure ML)
Scope
- Model Selection
- Text mining & image mining
- Association rules mining
- Data preparation
- Data preprocessing & visualization
- Data loading & transformation
- Classification
- Clustering
- Dataset enhancement
- Dimensionality reduction
- Regression
- Recommenders
- Distributed Linear Algebra
- Distribution
Scope
- Model Selection
- Text mining & image mining
- Association rules mining
- Data preparation
- Data preprocessing & visualization
- Data loading & transformation
- Model Selection
- Text mining & image mining
- Association rules mining
- Data preparation
- Data preprocessing & visualization
- Data loading & transformation
- Classification
- Clustering
- Dataset enhancement
- Dimensionality reduction
- Regression
- Recommenders
- Distributed Linear Algebra
- Distribution
Previous machine learning projects:
- Natural Language Processing project to parse and analyze human trading information
- Sales prediction algorithms based on historical data
- Predictive maintenance algorithms
- Image recommendations, using deep learning, computer vision, assisted and unassisted Learning large set of images
- Social network filtering and recommendation
- Computer vision components for driverless car systems
- Various virtual assistants (multi-intent language interpretation)
Previous machine learning projects:
- Natural Language Processing project to parse and analyze human trading information
- Sales prediction algorithms based on historical data
- Predictive maintenance algorithms
- Image recommendations, using deep learning, computer vision, assisted and unassisted Learning large set of images
- Social network filtering and recommendation
- Computer vision components for driverless car systems
- Various virtual assistants (multi-intent language interpretation)