2021 The Year of Transformers – Deep Learning
Transformers are a type of neural network architecture that has gained significant popularity due to their unwavering dedication to achieving optimal results in completing assigned tasks. Deep learning, which is widely recognized as a powerful tool, has significantly transformed the way we operate, proving to be both a lifesaver and a solution to disaster. Big players like OpenAI and DeepMind employ Transformers in their AlphaStar applications. …
Real-Time AI Powered Trends Business Can’t Survive Without in 2021
AI is getting more and more prominent across industries which is a plus point to move away from hype. It was once over-hyped for marketers, but now it’s the most powerful tools to automate their day-to-day operations. According to McKinsey, the AI industry is expecting to have more than $2.6 trillion worth of business in sales and online marketing. As most of the companies will seek an enhanced customer experience for their end-users, there will be tough competition against each other for a more stable future. Here are the top 5 AI-powered tools that businesses can’t sustain without in 2021.
Deep Learning Vs Neural Networks – Demystifying the Differences
Deep learning, also called a subset of machine learning which is a specialist with an extremely complex skillset in order to achieve far better results from the same data set. It purely on the basis of NI (Natural Intelligence) mechanics of the biological neuron system. It has a complex skill set because of methods it uses for training i.e. learning in deep learning is based on “learning data representations” rather than “task-specific algorithms.”
Deep Learning – Driving the Innovation in NLP
Natural language processing, one of the most important technologies of today’s information age. It’s everywhere and used on almost at every instance in daily life like emails, machine translation, google search, virtual agents etc. In recent times deep learning has obtaining too much attraction and respect from the industry which helps nlp to avoid traditional, task-specific feature engineering. The performance across many different NLP tasks, using single end-to-end neural model has achieved significant improvement.
Deep Learning – Introduction to Boltzmann Machines
The Boltzmann machine, a type of stochastic spin-glass model with an external field, has been subject to various nomenclatures including the Sherrington-Kirkpatrick model with an external field and the Ising-Lenz-Little model. The present work provides a demonstration of a deviation from the conventional Sherrington-Kirkpatrick model, which pertains to the realm of stochastic Ising models.
Deep Learning Algorithms — The Basic Guide
Deep learning leverages autonomous learning mechanisms that depend on simulated neural networks, commonly referred to as artificial neural networks (ANNs), to replicate the intricate cognitive operations of the brain implicated in information processing. During the process of training, algorithms endeavor to ascertain significant attributes, organize entities, and unveil consequential patterns within the data via the utilization of latent components in the input distribution.
Deep Learning – Introduction to Recursive Neural Networks
Recursive neural networks belong to the same family of models as deep neural networks, given that they can be seen as a modification of them. Usually, these results are produced by systematically applying a consistent set of weights to the arranged inputs in a repetitive manner. This occurrence happens consistently across all points due to identical causative elements. Recurrent Neural Networks (RNNS) are a group of structured designs that operate on directed acyclic graphs, tailored to handle organized inputs.
Artificial Intelligence – Some Basic Pointers
The current form of artificial intelligence is purely preliminary software. Scientists believe that this technology is still in the beginning stages, and further developments can have the capacity for changing the world. The current technology or weak AI can easily surpass human capabilities, while its more advanced forms have the power to make human workers obsolete.
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..
Machine Learning -Basic Terminologies in Context
The Machine Learning hype, too much information on the internet, and using ML terms by almost every tech show have actually created a “misinformation epidemic” of ML. It is revolutionizing the way we do our business and what should be done to improve upon it. ML develops its own encompassing strategy from the experience it comes across over the period. Mathematics, statistics, programming, and the common sense of human beings are now part of integral components of machine learning.
IoT Development – The Next Wave of Innovative Connectivity
All IoT use cases are not equal. The requirement for IoT data connectivity varies greatly depending on the requirements of different domains. There are scenarios where you cannot afford quick sensor discharge. For example, if you have a myriad of sensors deployed in an IoT-powered rent-a-bike business, you need a connectivity solution that does not cause the sensor to use a lot of power. Hence, you would need LoRa or SigFox connectivity solutions.
Artificial Neural Networks – Debunking The Myth
ANNs are an emerging discipline and they are the subject of research, study, and emulation for the information-processing capabilities of neurons of the human brain. Sadly many researchers are too quick and pivot the “Human Brain and ANNs” under one pin tip which is causing & creating huge confusion for newcomers. Their point in forms of discovery is entirely different though.
Data Science – Barriers and Challenges
Big Data is so big that it makes it difficult to analyse. For instance, cardholder data should be managed in a highly secured data vault, using multiple encryption keys with split knowledge and dual/triple control. Big data also presents a tremendous opportunity for enterprises across multiple industries especially in the tsunami-like data flow industries i.e. Payments and Social media.
Deep Learning – Deep Convolutional Generative Adversarial Networks Basics
Generative Adversarial Networks are a class of algorithms used in the unsupervised learning environment. As the name suggests they are called Adversarial Networks because they are made up of two competing neural networks. Both networks compete with each other to achieve a zero-sum game..
Important Characteristics of Good Customer Database Management
Customer Database Management – In modern times, companies deal with different types of data, and that too in large volumes. Hence, it is important to manage the data in such a way that it can be accessed conveniently and queried at any time.