Deep Learning and AI Services
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Artificial intelligence in deep learning
Machine learning solutions
Exploring Deep Learning as a Service
Cognitive technology, especially AI technology and its subsets, have contributed in unique ways in business. From the more obvious benefits of resource productivity, cost optimization, to the more detailed automation, business intelligence, and personalization, the role of Artificial Intelligence in business has been tremendous. And while all functions can be attributed to AI, there’s specific technology that’s being applied in each case. Here’s looking at the most common AI terms w.r.t. Deep learning technology.
Artificial Intelligence and
When we look at the difference between AI and Machine Learning, simply put, ML is a subset of AI. AI is adding intelligence to machines, with a set of algorithms so as to do tasks that would require human intelligence. ML on the other hand is training machines, to empower them to learn from experience, so as to do tasks without human intervention.
AI in Neural Networks
Artificial neural networks or ANNs are computer system, that have self-learning capabilities and can simulate how human brains receive, comprehend and analyze information. ANN is the key tool to machine learning solutions and can learn to deliver better results with the availability of quality and quantity of data.
Deep Learning and AI
What is Deep Learning? Deep Learning is an AI function that mimics the human brain in processing data. It creates patterns in objects, images, speech, etc. so as to assist in decision making. It can function without human intervention, and can work with large volumes of structured and unstructured data.
Deep Learning vs Machine
Deep Learning is a subfield of Machine Learning, or rather an evolved form of ML. Inspired by ANN, Deep Learning algorithms can identify patterns, classify them, and draw insights from it, just as human brains can. In ML systems, while learning comes through parsing and data-based learning, Deep Learning models function and make decisions much like the human brain.
Deep Learning Examples
The How and Where Deep Learning Applications work
At the root of any AI system lies the quality and quantity of data. Today, with the availability of volumes of data, Deep Learning applications in business have found new dimensions of performance. Whether to improve customer experience in customer support or user engagement in social media platforms, deep learning techniques are paving their path.
As a Deep Learning services provider at Day One, we aim to bring the innovations and technology home to our clients. The goal is to help businesses do more with AI, and now is a good time to start.
AI Virtual Assistants
Understanding language-based data for voice commands; speech recognition and more.
Having intelligent man-machine conversations by identifying speech, language, and intent.
Facial Detection & Recognition
Face identification for security, privacy, social media, identify verification, payments etc. with precision and accuracy.
Automated text/speech translation between languages, CNN based visual translation for images.
Image Processing, Predictive Maintenance, Driverless cars – it’s advanced deep learning in CV models.
Recommenders for Personalization
Recommend products based on personalized tastes, for upselling and cross selling.
Building a custom Deep
We believe that technology is for everyone. Our goal in offering Deep Learning consultancy services to businesses is to aid them in accessing the power of deep tech to scale. In our experience, most businesses fail to adopt AI solutions because of lack of adequate knowledge. AI is a vast field, and each tech has its unique offering. While Deep Learning in AI is changing dynamics across business processes and verticals, it is not always the solution to all business problems. When we collaborate, we help you to understand how deep learning works, how it helps business, and why it is (or not) the answer to your business challenge. Your business has a unique challenge and a custom solution is the only answer.
Financial Services and Banking
Sentiment analysis, text analysis, e-discovery, fraud detection, network security, portfolio analysis, product recommendation, customer support – it is the next level of service with Deep Learning systems.
Deep Learning for Cybersecurity
Security, malware detection, intrusion detection, spam identification, network traffic anomaly analysis, etc. The scope for Deep Learning applications is vast and expanding.
Deep Learning in
Smart manufacturing in factories is looking at Deep Learning solutions development for quality control, predictive maintenance, process monitoring, prototyping, premise security, and more.
AI and Deep Learning in
Use of distinct Deep Learning models like reinforcement learning. Used in 3D modeling, building cooling load prediction, rut prediction, safety guardrail detection, occupancy modeling, and more.