DEEP LEARNING SOLUTIONS
Deep learning allows computational models with several processing layers to learn multiple degrees of abstraction for data representations. Lets discover more!
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Each layer learns a notion from the input, which is then built upon by successive layers; the higher the level, the more abstract the concepts learnt. Deep learning, a machine learning technique based on artificial neural networks, has emerged in recent years as a powerful tool for machine learning, with the potential to transform the future of AI. In addition to its predictive capability and capacity to create automatically optimal high-level features and semantic interpretation from the input data, rapid increases in processing power, fast data storage, and parallelization have all led to the technology’s rapid adoption.
Deep Learning Applications
Real-world deep learning apps are a part of our daily lives, but in many cases, they are so well integrated with products and services that users are not able to comprehend the complex data processing that takes place in the background. Some of these examples include the following:
How does Conversation AI Work?
AI dialogue engages in contextual dialogue using natural language processing and other related algorithms. As one develops a larger user input chorus, your AI gets better at detecting patterns and making predictions. Conversational Al works with customers on four broad steps we will explore to get a better feel for this technology:
Voice/Text Recognition. Here, the user provides input either by voice or text.
Input analysis. If the input is based on the text, the original language (Natural-language understanding) is used to extract the meaning from the given words. If the input is based on speech, the automatic ASR speech recognition is first used to distinguish audio into unmodified language tokens.
Here, native language production is used to create an answer to user’s questions.
Here user inputs are analyzed to refine responses overtime to ensure that their responses are correct and accurate.
Types of Algorithms Used in Deep Learning
- Convolutional Neural Networks (CNNs)
- Long Short Term Memory Networks (LSTMs)
- Recurrent Neural Networks (RNNs)
- Generative Adversarial Networks (GANs)
- Radial Basis Function Networks (RBFNs)
- Multilayer Perceptrons (MLPs)
- Self Organizing Maps (SOMs)
- Deep Belief Networks (DBNs)
- Restricted Boltzmann Machines( RBMs)
Why Mobiloitte for your Deep Learning Solutions?
From machine learning to data analysis and neural networks, our technology covers every aspect of your development needs.
We use our state-of-the-art technology to create affordable solutions that can provide great support for business growth.
The Complete Solution
Where other organizations lack the skills or infrastructure to provide a complete solution, our product development services ultimately satisfy your needs from design to development, testing and marketing, all under one roof.
Most Effective Solutions
With industry-leading results and state-of-the-art service, Mobiloitte Technologies is developing highly efficient solutions that are built to last.