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The Limitations of AI Large Language Models: Why Human Intelligence is Still Essential

In 2017, researchers at Google published a paper that proposed a novel neural network architecture for sequence modeling. That architecture is known as the Transformer. The Generative Pretrained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) are the two most well-known types of transformers. In our article “ChatGPT: The Revolutionary Language Model Taking the […]

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ChatGPT: The Revolutionary Language Model Taking the World by Storm

“The best artificial intelligence chatbot ever released to the general public“, “Google killer“, and “Mind-blowing AI Chatbot” – such terms are beginning to appear in the media about ChatGPT, which has become a topic of conversation around the world. “ChatGPT was estimated to have reached 100 million monthly active users just two months after launch,

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Marketing Mix Modeling - czy Robyn by Meta zautomatyzował MMM?

Robyn is an open source project by Meta that aims (at least to some extent) to automate Marketing Mix Modeling. According to the authors, its goal is to, among other things, exclude human error and analyst subjectivity. In this article, I would like to describe its most important functions and share my own opinion on whether

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Speed up Python with Numba

In the last article, I discussed which Python design decisions limit its performance. In this writing, I will demonstrate the Numba package that addresses those limitations to provide high-speed performance for specific use cases, particularly when speeding up functions performing computations on the Numpy’s ndarrays. “Numba is a just-in-time compiler for Python that works best on code that uses NumPy

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Why is Python slow?

In this series of articles, I present some Python features that cause the execution time to be extended and some popular workarounds to make your code run faster. In the first part, I explain why Python is slower than low-level languages such as C or C++ and other high-level languages like Java or C#. Let’s

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One of the best books to get started with Data Science

Some years ago, during my studies at the University of Bonn, I had a Computational Statistics lecture. It was one of the elective courses within the Econometrics and Statistics specialization. Until today, you can read on the syllabus of this lecture: “The course explains ideas and methodological issues of computationally intensive statistical methods. There will

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3 sposoby na stworzenie modelu głębokich sieci neuronowych za pomocą Keras i Tensorflow 2.0 - sekwencyjne, funkcyjne i podklasowe API

In this article you will learn about three ways to create deep neural network models using Keras and Tensorflow 2.0 You will learn about their advantages and limitations, and see examples of how these methods are used. Keras and Tensorflow 2.0 provide three ways to build different deep neural network architectures: Sequential API Functional API

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Pętle, listy, sortowanie... Co dalej?

Most of the programming tutorials aimed at beginners emphasize learning fundamental code instructions like ‘for’ or ‘if’, enabling writing basic programs and algorithms. While it is a good idea to familiarize yourself with the nuances of your favorite programming language with such tutorials’ help, it won’t be necessary to go through essential programming rules every

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