Category: Artificial Intelligence

Gated Recurrent Unit

GRU – Gated Recurrent Unit Architecture

The foundational structure of the Gated Recurrent Units (GRUs) represents a recurrent neural network (RNN) architecture utilized within the realm of deep learning and also provides an enhanced computational advantage over the Long Short-Term Memory (LSTM), affording it a distinct preference in specific domains.

What are Neural Networks? | Strong and Jovial Plain Text

The human brain is an impressive feat of cognitive engineering, giving us the upper-hand when it comes to coming up with original ideas and concepts. We’ve even managed to create the wheel – something that not even our robot friends could do! This shows just how far we’ve come in terms of evolution – proving that humans are true masters of invention.

The Fundamentals Of Machine Learning

The main purpose of ML (machine learning) is to create an automatic data model for the purpose of analysis. Thus ML is to create a system that can learn from the data according to the algorithm used. The result can be found by mapping the output to the input or finding patterns/structures or learning by rewarding/punishing.


Payment Intelligence | Powerful And Strong Combo With AI

The fusion of Artificial Intelligence technology with payment processes has led to a remarkable enhancement in efficiency, creating a mutually beneficial partnership between the two domains. Artificial intelligence was acknowledged and employed before this era, although its utilization was considered inadequate. More research is necessary to clarify the correlation among blockchain, payments, financial technology, and artificial intelligence.

Conversational AI

Conversational AI – Powerful, Dangerous and Useful

The primary focus of conversational AI is on developing intelligent solutions that can understand human language, interpret user goals, and deliver customized replies that are relevant to the circumstance. Conversational AI integrates multiple disciplines, such as NLP, machine learning, and dialogue management, to offer diverse and immersive conversational experiences.

Deep Learning – Introduction to Artificial Neural Networks

LSTM – Long Short Term Memory Architecture

LSTM is used to solve issues with RNNs processing extensive sequential data. Calling LSTM as an advanced RNNs is not wrong. LSTMs excel in processing sequential data with long-term dependencies. LSTM is utilized for tasks like sentiment analytics, language generation, speech recognition, and video analysis.

Everything You Ever Wanted to Know About Artificial Intelligence

Artificial Intelligence is all about making machines smarter so that they can act and think like humans. Just look at the popularity of devices like smartphones, and smart fitness trackers to see how wholeheartedly consumers embrace products and services that can make their life smarter, easier, and more streamlined.

Top 5 Deep Learning Applications on Social Media For Businesses

Deep Learning – “It is undeniably mind-blowing” machine learning technique that teaches computers to do what comes naturally to humans: learn by example. It can […]

Not What You Think – Robots and Artificial Intelligence

Robot failure can occur for the basic and widely known reason that their machine learning models may not be precise enough or require extensive data and training to be precise. Robots excel in tasks that pose a substantial threat to humans, have low economic value, are menial in nature, and are significant in humanitarian endeavors with high risk involved. It is unlikely that robots or AI with advanced capabilities will replace our jobs in the next 50 years or beyond.

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Machine Learning – Challenges of Supervised Machine Learning

Supervised machine learning through historic data sets is able to hunt for correct answers, and the task of the algorithm is to find them in the new data. It uses labeled data with input features and output labels. The program uses labeled samples to identify correlations between input and output data. Output labels in supervised learning are called the “supervisory signal”.

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The Role of Powerful AI in the Future of Fintech

The advancement of technology and AI has allowed for the expansion of financial services beyond traditional banking. These endeavors have endeavored to clarify monetary services by focusing on precise and limited profit margins within this field. This statement refers to businesses that reach a large audience through multiple distribution channels, including mobile operators, manufacturers of mobile devices, retailers, and online marketplaces.

Smart Payments

Data Science and Smart Payments

The infiltration of AI technology is causing significant transformations in various industries, such as finance, healthcare, and science, resulting in a global paradigm shift. Organizations must exercise the same level of caution in handling their data as they do with their finances.

eCommerce Transformation

Artificial Intelligence | A Hack for eCommerce Transformation

Artificial intelligence has become a significant factor in e-commerce’s current scenario. This study delves into the possibility of utilizing artificial intelligence (AI) to enhance individualized shopping encounters for customers in the retail sector. The study focuses on how retailers can use artificial intelligence technologies to improve customer gratification, allegiance, and interaction.

AI Hero FinTech

AI Bond With FinTech | A New FinTech Emerging

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.

Machine Learning Models and L1 and L2 Regularization

rtificial Intelligence has changed the face of world technology. It is divided into multiple sub-fields as robotics, machine learning, natural language processing, and many more. All these fields had vastly contributed to the development of smartphones, computers, software, and other smart machines. Machine learning is a sub-field of AI which involves research and study based on computer algorithms.