logo

Technology to facilitate business

The Modern World of Data Centers

By Keith Engelbert, Chief Technology Officer,...

The Modern World of Data Centers

The Triple Bottom Line and Data Centers

By Rob Nash-Boulden, Director, Data Centers, Black...

The Triple Bottom Line and Data Centers

CHANGE OR DIE- AND THIS CHALLENGE STARTS WITH YOU

By Matthew Stockwin, Manufacturing Director, Coats...

CHANGE OR DIE- AND THIS CHALLENGE...

The Chicago Housing Authority Collects, Monitors and Reports Big Data for Energy Benchmarking Compliance

By Ellen Sargent, Director of Sustainable...

The Chicago Housing Authority...

Why Deep Learning is Significant to Enterprises

By Enterprise Technology Review | Thursday, July 23, 2020

Deep learning enables largely unsupervised learning against unstructured data to return hidden signals. It will free up the time of in-demand data experts to connect insights to action.

FREMONT, CA: A new decade offers a natural delivery point around business transformation – a change that is frequently being fueled by real-time business decisions. As brands face a 2020 reality check to set their next-decade strategy, investments in evolving and emerging trends and technologies are giving organizations a competitive edge.

The tangible results of these cases have increased through a subset of machine learning with expanded neural networks that learn from unstructured data.

The function of AI, deep learning relies on training through data representations, rather than the classical ML variant of task-specific algorithms. In simplest terms, deploying a deep learning technology permits the network to perform largely unsupervised learning against the swaths of data that return the hidden signals.

This trend is rapidly being adopted within the business analytics world due to enhancing cloud architecture of big data that is readily accessible.

Making sense of the signal returns poses a challenge for the data science world that is the interpretation of meaning. There has never been a more connected and rapidly expanding universe of unstructured data to exploit business purposes. Yet, very few enterprise analytics organizations delve into the potential to disrupt their current progress with these maturing capabilities.

Scarce data scientists stretched capacity with exploratory work, made worse by the growing focus on short-term results that demand priority. At present, the spotlight on deep learning will be the nexus between the knowing and doing as this technique becomes widely experimented and worked to provide autonomous functions within finance, marketing, operations, and supply chains at a computer power speed.

The practical advent of deep learning to predict and understand human behavior is a storm disruptor in how the companies will perform with intelligence against the competitors. Data is arguably a strategic asset, and now the enterprise can begin to drive a wedge in how insights translate to business performance without adding more human capital.

See also: Top Machine Learning Technology Companies

Top