Data Science and
Machine Learning
#CNN #RNN #optimization #classification #keras #clustering #k-NN
#inference #random_forest #boosting #tensorflow
Data Science and
Machine Learning
Modern economics and businesses do rely hugely on data: we make assumptions, build models and validate them using data and proper data science techniques. It's true that whoever has the data owns the world. But the one who properly applies it to build new systems, optimize decision-making and customer satisfaction — they drive the changes and get the tastiest piece of cake
Modern economics and businesses do rely hugely on data: we make assumptions, build models and validate them using data and proper data science techniques. It's true that whoever has the data owns the world. But the one who properly applies it to build new systems, optimize decision-making and customer satisfaction — they drive the changes and get the tastiest piece of cake
Here at Simlabs we know how to tackle complex data-science issues. We support academic research in the field of deep learning, and we have solid experience in building machine-learning models to address particular challenges. Contact us now, we'll help your data accelerate your business!
Here at Simlabs we know how to tackle complex data-science issues. We support academic research in the field of deep learning, and we have solid experience in building machine-learning models to address particular challenges. Contact us now, we'll help your data accelerate your business!
Predictions and hints
The key value of data-based predictions and hints are to keep the user focused on what's really relevant. For example, properly-designed and implemented prediction systems can save up to 80% of a controller's attention, resulting in increasing engagement and potentially saving hundreds of lives.
Data extraction and clustering
Sometimes you have lots of data but you can't figure out what to do with it. Together, we can go through what you need, clean it, analyze and group it, find inconspicuous relationships, and reduce dimensionality. In the end, even visualizing trends is sometimes hard! As data-scientists, we are here to help you.
Artificial Intelligence and bots
The most promising part is the decision-making automation. Some domains do still need human-controlled decision making, but a huge number of industrial challenges are possible to be solved with either random forest trees or some combination of deep/recurrent neural networks. Through the production mix of academic research and software engineering, we have made an aircraft bot which can take-off and land safely, while minimizing fuel. This is a strong point.

Other Solutions
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