CloudStakes Technology

  In the past few years, we have seen the advancement of developer tools and platforms for technologies like machine learning and artificial intelligence in industries, including banking, finance, healthcare, and more. Also, AI developers have tried several techniques, from utilizing cognitive cloud-based APIs, framework libraries to trained models only to integrate AI capabilities into applications. Developers (i.e., AI engineers and researchers), in the end, have decided to choose a suitable machine learning framework in order to train their ML models.        The reason behind choosing the ML framework is to make the development process of machine learning models faster and smoother. These tools minimize developers' ML deployment efforts and reduce overall ML model development time. However, organizations can design ML framework according to their needs. In most cases, they choose to use the existing one that matches their demands.    Thi...

The rise of Artificial Intelligence and Machine learning technologies have advanced the automated processes of application development and quality assurance to a great extent. AI and ML have influenced our routine activities and lives by providing smart products, like Alexa, Chatbots, Facial Recognition devices or software, and many others. It can be said that their interference or influence in our lives have made our works a lot easier. And most importantly the quality and variations of products also have increased. With the increasing variations in product choices, customers are also confusing and fluctuating their demands in the influence of better-promised alternatives available in the market. Let’s understand this point through the survey of customers’ market switch behaviour, a group of 100 customers buys one product from shop A, and all of them are getting the worst product experience, and 91 of them does not even bother to complain about the worst product and leaves that matter...