A significant driver of deep learning is the availability of large datasets and the ever-improving hardware. They enable models to be trained with many millions of parameters.
Deep learning with Basefarm
In our ideation and scoping workshop we identify data science use cases step-by-step, assess their feasibility and prioritize them in respect of added value and expenditure.
Why Basefarm?
We believe there is no such thing as a ready-made solution. For our clients we develop customized deep learning solutions based on state-of-the-art processes. We deploy the right architecture for different problem domains, for example convolutional neural networks (CNNs) for image recognition or recurrent networks (RNNs) for analyzing sequences such as time series. This approach ensures each client receives the optimal solution, whether that is B2C or B2B.
Our Data Science Team possesses extensive sector-spanning experience in the field of machine/deep learning. With a mix of mathematicians, psychologists, physicists and computer scientists, the team is able to examine the various facets of a data problem from a wide range of angles. We stay on the cutting edge of research and do not shy away from technical innovations.
Big data Blog
CASE STUDY:
DATA THINKING
AT C-LEVEL
- Project: Capability assessment and development of a data maturity roadmap for an international retail holding
- Approach: Workshops and individual interviews with business units and IT;
“ There are no best practices out there
– just practices to learn from and get inspired by.”
– Florian Dohmann, Senior Data Scientist
- Capability Assessment – unique model for the evaluation and analysis of operational and organizational skills and competencies within a company (data, algorithms, technology, mindset), fit gap analyses, determination of key insights and recommended actions
- Results: Identification and prioritization of recommended actions, data maturity roadmap (planned for 24 months)