Big data offers the great opportunities and transformative potential for various areas such as e-commerce, healthcare industry manufacturing, social network and educational services. Therefore, deep computation, a novel area, has attracted great interests of researchers in recent years. It refers to a systematical model for big data representation, storage, analytic and mining based on tensor theory. The characteristics of big data make the feature learning such an extremely challenging task that conventional data mining methods are almost impossible to address. On one hand, the unprecedented data volumes require the scalability of feature learning algorithms for big data.
Why we need it: High variety demands the feature learning algorithms which can learn the complex correlations among heterogeneous data to form an effective representation of big data. Therefore, it needs urgently new innovative theories and advanced technologies for feature learning on big data. Today, deep learning, together with advances in high performance computing, provides a new innovative solution. There are various deep learning companies those provide efficient services in this field.
Services: Deep learning refers to a set of machine learning models that perform supervised/unsupervised feature learning to automatically form hierarchical representations in deep architectures. The most typical deep learning model is the stacked auto-encoder (SAE). Furthermore there are more deep learning algorithms available. These are:
- 1. Stacked auto-encoder (SAE): It is established by stacking auto-encoders such as Restricted Boltzmann Machines, sparse auto-encoders, denoising auto-encoders and predictive sparse coding. SAE uses a large number of unlabeled data to learn the latent features in each hidden layer by a greedy and efficient layer-wise pre- training and a small amount of labeled data for fine-tuning.
- 2. CNN: Convolutional Neural Network is a biological inspired network comes under multi layers perceptron’s. It is comprised of one or more convolutional layers and then followed by one or more fully connected layers as in a standard multilayer neural network. Main benefit of is that they are easier to train and have many fewer parameters than fully connected networks with the same number of hidden units. Infinite Research Solution is the best company which provides deep neural network services.
- 3. RNN: A recurrent neural network is a network in which neurons sends feedback signals to one another. A RNN has loops in them that allow information to be carried across neurons while reading in input. Long term short memory and GRU are its type. Infinite Research Solution is the best Artificial Intelligence Company in India. Therefore, At Infinite Research Solution we deal with all types of algorithms of deep learning services and always try to provide excellent services to the clients.
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