Deep learning is an exciting field that is poised to revolutionize the way data science is done. As AI and machine learning continue to advance, data science will become more powerful and will be able to tackle more complex and real-world problems. One of the key drivers of this change is deep learning, which is made possible by neural networks.
Deep learning systems use layers of neural networks to enable machine learning at scale, with big, raw datasets. This means that we can finally harness the type and size of data needed to inform these applications and produce human-equivalent results. This makes machine learning capabilities much more accessible, as the human is further removed from the process in deep learning, as it can also use labelled datasets for unsupervised learning.
Some examples of how deep learning is being used in the real world are predictive maintenance, fraud detection, customer segmentation and network optimisation.
However, there are some common challenges that organizations face when adopting deep learning. These include the need for specialised skills, the high cost of deploying a fully trained deep learning model, and the need for more data management.
Brytlyt is an innovative platform that addresses these challenges. Brytlyt brings data science, analytics, and visualisation together in one platform to tackle these challenges. The GPU platform easily slots in to accelerate data science tools, and with advanced in-database AI, it makes machine learning and deep learning more accessible. With an advanced in-database AI solution built on PostgreSQL and PyTorch technology, Brytlyt can seamlessly slot into pre-existing tech stacks whilst supporting deep learning, traditional machine learning and external frameworks. This allows organizations to overcome the challenges of adopting deep learning, and take advantage of its powerful capabilities
Download our whitepaper on creating a confident and accessible deep learning future to learn more.
The Rise of Accessible Data Science
A Whitepaper on Deep Learning for a Confident Future
