Machine and Deep Learning Services
We help organizations to create highly customized solutions based on supervised, semi-supervised and unsupervised learning techniques, improving average accuracy of a ML-models and (or) integrate it to client platforms and systems.
Machine Learning algorithms
Machine Learning libraries & frameworks
1 Business Analysis
1. Identifying business problem and expected value
2. Conduct exploratory data analysis
3. Prioritize modeling criteria
4. ML-solution implementation strategy preparation
5. Evaluate risks and success criteria
2 Data Preprocessing
1. Explore, clean, split, and shape the existing data for training enhancing its quality
2. Produce clean and well-curated data which leads to more practical and accurate model outcomes
3. Find and eliminate any data leakage
3 ML-model Building
1. Repeat the process of training the models and evaluating their efficiency until the required accuracy is achieved
2. Tune model hyperparameters for improved performance
3. Adapt the models to new data and discover new patterns
4. Deploy ML models to necessary environment
4 Business intelligence
1. Fully-validated model that you can use to create your software product, complete with AI-features
2. Delivering ML output in an expected format and relevant documentation artifacts
3. Visualize data outputs of model execution to generate actionable business insights and create interactive reports
5 Support and maintenance of ML-models
1. Adopting the models based on changes that are introduced by humans and which could impact the model
2. Relearning the models on a new (not outdated) data
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Innovative Future, Inc.
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