Article
Transformers, even though released in 2017, have only started gaining significant traction in the last couple of years. With the proliferation of the technology through platforms like HuggingFace, NLP and Large Language Models (LLMs) have become more accessible than ever. Yet - even with all the hype around them and...
David Landup
Deep Learning models are very versatile and powerful - they're routinely outperforming humans in narrow tasks, and their generalization power is increasing at a rapid rate. New models are being released and benchmarked against community-accepted datasets frequently, and keeping up with all of them is getting harder. Most of these...
Keras is a high-level API, typically used with the TensorFlow library, and has lowered the barrier to entry for many and democratized the creation of Deep Learning models and systems. When just starting out, a high-level API that abstracts most of the inner-workings helps people get the hang of the...
Let me preface the potentially provocative title with: It's true, nobody wants overfitting end models, just like nobody wants underfitting end models. Overfit models perform great on training data, but can't generalize well to new instances. What you end up with is a model that's approaching a fully hard-coded model...
In this tutorial, we are going to talk about a very powerful optimization (or automation) algorithm, i.e. the Grid Search Algorithm. It is most commonly used for hyperparameter tuning in machine learning models. We will learn how to implement it using Python, as well as apply it in an...
Muhammad Junaid Khalid
Nowadays, we have huge amounts of data in almost every application we use - listening to music on Spotify, browsing friend's images on Instagram, or maybe watching a new trailer on YouTube. There is always data being transmitted from the servers to you. This wouldn't be a problem for a...
Ali Abdelaal
This is the 22nd article in my series of articles on Python for NLP. In one of my previous articles on solving sequence problems with Keras, I explained how to solve many to many sequence problems where both inputs and outputs are divided over multiple time-steps. The seq2seq architecture is...
Usman Malik
This is the 21st article in my series of articles on Python for NLP. In the previous article, I explained how to use Facebook's FastText library for finding semantic similarity and to perform text classification. In this article, you will see how to generate text via deep learning technique in...
This is the second and final part of the two-part series of articles on solving sequence problems with LSTMs. In the part 1 of the series, I explained how to solve one-to-one and many-to-one sequence problems using LSTM. In this part, you will see how to solve one-to-many and many-to-many...
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