Deep Learning Software

Deep Learning is an advanced subset of modern Artificial Intelligence (AI) tools that can teach machines to think, learn, and make decisions like humans. Deep learning works through complex Deep Neural Networks (DNNs) modeled after the human brain to recognize patterns in images, audio, and text to determine meaningful insights and make predictions.  Deep learning can be used to automate tasks that typically only humans can perform, such as translations, transcriptions, or accurate descriptions and classification of objects or text.

Deep learning differs from Machine Learning (ML) platforms in that deep learning learns from insights and errors without any human intervention, while ML requires algorithms trained on labeled data and rules to facilitate learning and automation in machines.

Key Use Cases for Deep Learning

• AI Voice Assistants: Deep learning analyzes human voices with speech recognition to understand nuances such as tone of voice, language, and accents. Using this analysis, this technology can model human voice patterns, understand intonations, and mirror speech rates to create the lifelike voices used in numerous application interactions, such as Siri or Alexa.
• Customer Service Chatbots: Deep learning and AI are used to build and train chatbots that can interact with customers and provide support with human characteristics. Chatbots are trained on vast data sets, can provide information, and even perform tasks to serve customer needs thanks to deep learning.
• Computer Vision: With deep learning technology, computers can see, comprehend, and classify objects based on the meaning and insights extracted from images and videos.
• Image Recognition: Deep learning algorithms are trained on massive data sets of images and then use this data to recognize and identify similar images. This technology has varying applications, from helping customers find products to helping autonomous vehicles identify signs, objects, or pedestrians on the road.
• Cybersecurity & Fraud Prevention: Deep learning has use cases across the cybersecurity industry for monitoring fraud patterns and trends to help defend systems and data against future cyberattacks.
• Recommendation Engines: Deep learning recognizes and learns from patterns and has the ability to learn over time, which is why this technology is used in many recommendation engines on websites and streaming platforms to show customers other products they may be interested in purchasing, or suggest shows or movies they may like to watch.
• Advanced Analytics & Forecasting: Deep learning continues to improve both prescriptive and predictive analytics for big data, and it is used in advanced predictive analytics tools to help organizations forecast sales patterns, future customer needs, supply chain changes, and more.