Skills that Will Help You Become a Better Engineer
Everybody talks a lot about hard skills to become an engineer. But what soft skills do you need to become a better at your job?
Hello everyone! In this category you will find features and opinion pieces about Natural Language Processing, Machine Learning, AI, and everything related. We will discuss the impact that Artificial Intelligence has on our everyday life and how we can make the most out of it. We will discuss current trends in the industry, and even try to guess what the future holds. The blog posts you will find in this category are a little less technical, but, in my opinion, among the most interesting ones. So please, share your opinion and your point of view on any one of these issues. I love to get the discussion going! And if you have a request for specific features or opinion pieces, tell us about it!
Everybody talks a lot about hard skills to become an engineer. But what soft skills do you need to become a better at your job?
We looked at PyTorch vs TensorFlow in depth. But what exactly is the difference between Keras and TensorFlow? And how do you implement Machine Learning projects in Keras and TensorFlow?
TensorFlow and PyTorch are two widely used frameworks for Deep Learning. But how to choose? Which performs better in which situation? Let’s see PyTorch vs TensorFlow in action!
There are many Deep Learning frameworks out there. But which one is the best framework for Deep Learning? Opinions vary on the matter, so let’s try to see a bit clearer.
BigScience is an open science Language Model trained on 1.5 TB of text data in 46 languages. But how has such a large and diverse dataset been built?
On Friday, March 11, 2022, HuggingFace launched training for their BigScience Large Language Model. Let’s have a look at the project and see what this means for NLP.
You might be wondering if Natural Language Processing is the right path for you. I decided to share my journey and what drove me towards Natural Language Processing to help others who might be in doubt.