Role of Convolutional Layer in Convolutional Neural Networks
The indispensable feature of convolutional neural networks, also denoted as CNNs, is the convolutional layer, which is commonly perceived as the pivotal and fundamental component that confers CNNs their appellation. The current layer is engaged in conducting a computational procedure commonly known as a “convolution”. After the successful initialization of all variables and assigning them with random values, the image of a deer is utilized with specific parameters..
Deep Learning – Introduction to Artificial Neural Networks
Deep Learning uses neural networks to create the foundation of the working model architecture. A neural network that took the idea of the human brain working for its basic working model has its basic unit a neuron. Like the human brain artificial neural networks mimic a similar information processing model i.e.:
Deep Learning – Introduction to Convolutional Neural Networks
Convolutional neural networks (CNN) are based on simple principles of science and math, even though they may seem complicated to some. When a filter is applied to the input, it will cause the activation to happen. This is a simple and easy thing to do. A feature map is made by using a filter many times on an input. This shows where the features are and how strong they are in the input.
Demystifying Deep Learning – Back to Basics
Deep Learning (DL) employs multiple layers of non-linear training units in order to facilitate feature extraction and transformation. The phenomenon of artificial intelligence has induced significant transformation in contemporary enterprises due to its demonstration of a degree of accuracy in specific endeavors that is akin to human capabilities. A variety of tasks, including but not limited to design acknowledgment, pattern recognition, picture classification, and voice/text interpreting, are frequently employed in the respective field under consideration. Self-driving CAR is one of the best examples and biggest achievements so far.
Uncovering Anxious Deep Learning for Ease
A technique for implementing machine learning. At the same time I also claim It is absolutely wrong to call Deep Learning as Machine Learning (in my personal opinion). The techniques is to achieve a goal not necessarily come out of same goal. #AILabPage
World Wide Data Wrestling
Big data presents a tremendous opportunity for enterprises across multiple industries especially in the tsunami like data flow industry of “Payments”. FinTech, InsureTech, MedTech are major data generating industries i.e massive group of factories. According to some data from Google it shows technology based innovative insurance companies
AI Changing FinTech Modus Operandi
AI in Fintech is a great help & ease for understanding on how the automation can be achieved for automated tasks (yes its true). Machine Learning focuses on predictions, based on known properties learned from the training data using too much statistical inductive reasoning. It’s been said ML works very well as long as past gets repeated in future. Financial chat bots use predictive analytics to push out real-time, informed responses to customers without the need for human intervention.
Magic Word Pay in Digital Payments
Today’s consumer expects a seamless mobile payment experience; failing to meet those expectations can be devastating to a brand, idea, innovation and eventually the payments industry. The world’s best companies; main from out side of payment / financial domain are rushing (yes rushing) for Digital Transformation for money. Getting inspired by the cutting-edge technologies, innovative products and solutions
Internet of Things – Mobile Financial Services
As on date the most common use for sensors is telematics, which allows devices installed in cars (car tracking devices) to transmit location data to owners and insurers. This also includes ability to track-stolen vehicle and help in recovery, automatic crash notification, and vehicle data recording force full actions by controller over telematics infra. Telematics also extends to tracking ships, car and trucks for fleet management and route optimisation. IoT merged with mobile financial services can ensure you can get fuel
Convolutional Neural Networks – Basic Info
The Convolutional Neural Network, CNN for short, is a powerful automated technology that supports a range of functions like self-driving, analyzing medical images and processing natural language. This software has exceptional efficiency in handling large and complex data sets.
The Rise Of Convolutional Neural Networks
The neural network’s architecture entailed a simplistic design, consisting of five layers comprising of convolutional layers with a dimensionality of 5×5 and max-pooling operations with a 2×2 size. The convolutional neural network architecture was designated as “LeNet” in honor of its creator, Yann LeCun.