Machine Learning coding is considered to be the easiest of all coding landscapes whether you choose Python, Java, or R . We are aggressively moving to the era of minimum coding with maximum efficiency where we have tons of endpoints,
AI explainability (XAI) continues to challenge business to explain underlying reasons of a ML model behavior. With the advancement of various algorithm such as DL (Deep Learning – ANN, RNN, CNN, GPT, LSTM etc.) predictability has been increasing while inferabilty/explainability
Artificial Intelligence and related terms such as Cognitive computing, Data Science, Robotics, Predictive Analysis, Machine Learning etc. have been drawing attention over the past few years of almost all institutions and not limiting to only business, technical or academics. AI
Back up process has been in our IT ecosystem for ages. Over the period of time people has been using “backup process” as a term interchangeably for synchronization, data transfer, copying data files and also while developing HA (High Availability)
Context: Digital economy needs much better network capacity (bandwidth) and broader coverage (access) than what is mostly available today. We have estimated the projection of 50 Billion devices talking to each other by 2020 in the course of IoT evolution.
IT landscape is transforming very fast, getting better, faster and cost efficient enabling business become more innovative and competitive while changing the social life dynamics. This is caught in the swirl of increasingly complex information with increasing infrastructure that is
Before we barge into adopting cloud solution to optimize our resources and reduce TCO, lets us understand the problem statement here. In IT landscape Cloud is clearly an enthralling and rewarding solution. Its scalability, availability, flexibility, customized or “Pay-as-u-Go” and