Artificial Intelligence

Augmented reality (AR) is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sound, or other sensory stimuli delivered via technology (Hayes 2021). Augmented Reality technology has seen unprecedented growth in 2021 (Makarov 2021). The market for AR technology is worth 15.3 billion US dollars. Due to greater app support, … [Read more...] about AUGMENTED REALITY AND MARKETING

Before proceeding with the indicator’s code, we have to code two simple functions:def deleter(Data, index, times):for i in range(1, times + 1):Data = np.delete(Data, index, axis = 1)return Datadef jump(Data, jump):Data = Data[jump:, ]return DataNow, we are ready for the code. Remember to have an OHLC array ready. You can see how to import an OHLC automatically in a previous … [Read more...] about The Fibonacci RSI. An Interesting Combination in Trading.

In this particular post, we will learn how to develop an image classifier predictive model using the teachable machine google project. This google project helps anyone to develop a machine learning model without ML expertise. Web and mobile apps can use these generated models.We will use a flower data-set to develop an image classification.Access the flower data-set in the … [Read more...] about How to create an image classifier predictive model without a single line of code?

Classifying Indian currency notes using their images and deep learning.Photo by Alexander Barton for NJI Media on DribbbleCurrency notes have identifiers that allow the visually impaired to identify them easily. This is a learned skill.On the other hand, classifying them using images is an easier solution to help the visually impaired identify the currency they are dealing … [Read more...] about Indian Currency Notes Classifier — on cAInvas

Using the Effective Number of Samples for Each Class to Re-Balance the Loss, Outperforms Focal Loss in RetinaNetIn this paper, Class-Balanced Loss Based on Effective Number of Samples, (CB Loss), by Cornell University, Cornell Tech, Google Brain, and Alphabet Inc., is reviewed. In this paper:A re-weighting scheme is designed that uses the effective number of samples for each … [Read more...] about Review — CB Loss: Class-Balanced Loss Based on Effective Number of Samples (Image Classification)