Artificial Intelligence

Automation and AI can be applied to innovate products, automate processes, and improve customer experiences, often by making predictions. Those predictions can produce tremendous value for the business but predicting the future is inherently difficult.The components of the automation tasks may be doing something relatively straightforward, such as using OCR (optical character … [Read more...] about 3 Common Mistakes Automation and ML Modelers Make

Artificial intelligence (AI) has become a well-known word across multiple businesses in recent years. AI is so popular that the International Data Corporation expects global spending on AI systems will grow from $35.8 billion in 2019 to $79.2 billion in 2022.As leading tech companies continue to show interest in AI investment, users will continue to see the technology become … [Read more...] about How AI is making Mobile App Personalization?

Build naive spam classifier using naive BayesIn our daily life, we get lots of emails. Some emails are useful and some are not. An unsolicited email sent in the bulk is a spam email. We do not generally want spam emails, so spam classifiers throw them in spam folders before they appear in our inbox section.According to Statista, around 29% of the emails sent in 2019 are spam … [Read more...] about Spam Classification using Naive Bayes Algorithm

In the last article, we discussed the MUSESelector. This kydavra selector performs feature selection based on a data frame. The biggest drawback of this method is that it is good only for binary classification problems. There comes into play an extension of this method — M3U — (Minimum Mean Minimum Uncertainty), implemented in kydavra as M3USelector, for multiclass … [Read more...] about Select features taking in account distribution with Kydavra M3USelector

Note that for each of the results you saw, they only used one picture taken from any angle. It was then sent to the model in order to produce these results, which are incredible to me when you think of the complexity of the task and all the possible parameters to take into consideration just regarding the initial picture. Such as the lighting, the resolution, the size, the … [Read more...] about ShaRF: Take a Picture From a Real-Life Object, and Create a 3D Model of It

If you want to stay on top of the latest distributed training with PyTorch and Ray, this is a healthy intro:“Transformers interpret allows any transformers model to be explained in just two lines. It even supports visualizations in both notebooks and as savable html files.”So for example if you were doing sentiment analysis on the sentence below:“I love you, I like you”This … [Read more...] about The NLP Cypher | 02.21.21

This is an awesome addition, which combined with our proprietary FAL NFC Tag technology, pin-points the art, telling you what it is and who its by, and giving you the art story.This creates amazing opportunities, not only for anyone to learn more about art and for artists to authenticate their works and tie their physical work to its FAL art blockchain catalog, but also for art … [Read more...] about FAL Launches Art Recognition™: Art Appreciation with a Snap of Your Mobile Phone Camera!

Role of Artificial intelligence in Architecture.Artificial Intelligence and architecture will come together to solve challenges with housing, the way we live, and cites. About 55% of the world’s population is living in urban areas or cities. By 2050, that figure is estimated to rise to 68%. Experts are expecting a dramatic upswing towards cities, which will cause countless … [Read more...] about Artificial Intelligence and Architecture.

Örnekleme Nedir ?Örnekleme istatistikte kesin olarak belirlenmiş bir kütleden alınan kümeyi ifade eder. Örneğin; Türkiye’deki tüm fabrikalar bir kütle iken İstanbul daki fabrika sayısı bu kütleden alınmış bir örnektir.En önemli özelliği temsili ve yansız olmasıdır. İnsanlar çoğu kez kararlarını alırken örneklemden yararlanırlar.Neden Örneklem Önemlidir ?Bilimsel araştırmalarda … [Read more...] about Python’da Örneklem Teorisi Uygulama

Who said so? The math says soI’m going to explain here is how to answer questions about neurobiology with an 80% probability that you will give the same answer as a neurobiologist. So let’s go.So here’s a neuron. It’s got a cell body. And there is a nucleus.Neurons, like other cells, have a cell body (called the soma). The nucleus of the neuron is found in the soma. It includes … [Read more...] about Neural Nets: “All great ideas are simple”