Advantages and Challenges of Deep Learning

Deep learning is a set of machine learning algorithms that model high-level abstractions in data using architectures consisting of multiple nonlinear transformations. What does it mean? How Deep Learning Works A deep machine learning process consists of two main phases: training and inferring. You should think about the training phase as a process of labeling

What is the Difference Between AI, ML, and DL

By the end of article, you will understand on what is the Difference Between AI, ML, and DL. Artificial intelligence is the future. Artificial intelligence is science fiction. Artificial intelligence is already part of our everyday lives. All those statements are true, it just depends on what flavor of AI you are referring to. For

Why Application Security Cannot Be Overstated

Deep learning is one of the buzziest buzzwords of 2017, and for good reason. Deep learning (more accurately called deep neural networks) attempts to mimic the activities of the brain. The basic principles of neural networks have existed since the late 1950s, yet it wasn’t until around 2010 that computers became powerful enough (and data

Introduction to Deep Learning Security

Cyber-security is a fast developing industry. As hackers become more and more sophisticated with all the types of attacks, so too must the protection offered by cyber-security companies. Security is set to unveil their new deep learning technology this fall which will take the company’s cyber-security solution to new heights. To understand the magnitude of

Definition of Deep Learning you should know

An artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in Artificial Intelligence (AI) that has networks which are capable of learning unsupervised from data that is unstructured or unlabeled. Also known as Deep