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- deepsense.ai, Inc.
- 2100 Geng Road, Suite 210
- Palo Alto, CA 94303
- United States of America
Poland
- deepsense.ai Sp. z o.o.
- al. Jerozolimskie 44
- 00-024 Warsaw
- Poland
- ul. Łęczycka 59
- 85-737 Bydgoszcz
- Poland
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- contact@deepsense.ai
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Five trends for business to surf the big data wave
/in Big data & Spark /by Konrad BudekAccording to IDC analysis, 16,3 zettabytes of data were created worldwide in 2017. Such volume shows why keeping an eye on big data business trends is so crucial.
Spot the flaw – visual quality control in manufacturing
/in Data science, Deep learning, Machine learning /by Konrad BudekHarnessing the power of AI’s image recognition and deep learning may significantly reduce the cost of visual quality control.
What is the best method of efficiently training machine learning for teams?
/in Data science /by Kamila StępniowskaThe tailored Team Training Tracks (4T) method is a way of teaching data science by working with a specific team on selected real-life projects in a company. It facilitates an effective learning experience for adults addressing an increasing job market need for data scientists.
How to start with machine learning wisely and become a data scientist?
/in Data science /by Kamila StępniowskaHow we teach data science now has many limitations. Universities, bootcamps and online courses have yet to provide an optimal learning experience that answers job market needs. A fourth way is needed.
Why do we need more data scientists and why should you become one?
/in Data science /by Anna KowalczykThe number of data scientists has grown over 650% over the past five years. Machine learning and deep learning skills are in huge demand at present, and the list of reasons you should join those already working in the profession is broad.
Artificial intelligence imagining and reasoning about the future
/in Data science, Deep learning, Machine learning /by Anna Kowalczykdeepsense.ai ML team has been working with Google Brain on helping AI imagine and reason about the future. They started from optimizing TensorFlow’s infrastructure for reinforcement learning and moved to end-to-end training of AI entirely on Google’s newest Cloud TPUs.
Starting deep learning hands-on: image classification on CIFAR-10
/in Deep learning, Neptune /by Piotr MigdalTired of overly theoretical introductions to deep learning? Experiment hands-on with CIFAR-10 image classification with Keras by running code in Neptune.
Image classification sample solution for Kaggle competition
/in Deep learning, Neptune /by Jakub CzakonWe’ve open sourced image classification sample solution that lets data scientists start competing in the currently running Kaggle Cdiscount competition.
Using deep learning for Single Image Super Resolution
/in Data science, Deep learning /by Katarzyna KańskaWe apply three different deep learning models to reproduce state-of-the-art results in single image super resolution.
Fall 2017 release – launching Neptune 2.1 today!
/in Data science, Deep learning, Machine learning, Neptune /by Mariusz GądarowskiWe’re thrilled today to announce the latest version of Neptune: Machine Learning Lab. This release will allow data scientists using Neptune to take some giant steps forward. Here we take a quick look at each of them.