FNNs are one of the simplest neural network types that can be utilized to move data and information in a single direction through multiple input nodes until the data reaches the output node. Our neural network engineers utilize Feedforward Neural Networks as standard networks that help in data classification and regression.
When it comes to image and video analysis, Convolutional Neural Networks (CNN) are an ideal choice for our neural network developer. Businesses utilize CNNs for many advanced AI applications, including facial recognition, text digitization, and natural language processing (NLP).
Recurrent Neural Networks (RNN) can be a suitable neural network for rule-based, sequential, or repetitive tasks involving image recognition and natural language processing. This type of neural network is often used to predict the outcome based on the user input. Some other use cases of RNN are time series prediction, voice recognition, and speech recognition.
Our knowledgeable and skilled neural network experts hold expertise in dealing with long sequences of data by utilizing LSTM networks. Natural language processing, time series analysis, and speech recognition are some of the applications for which we use LSTM neural networks.
Deep Neural Networks or Deep Learning Models are multi-layer neural networks, leveraging the capabilities of which our neural network developers can handle intricate patterns and large datasets. Deep Neural Networks (DNN) is an evolving trend in the autonomous industry as it is well-suited for tasks where data representation and high-level understanding are essential.
