Object Detection for Images and Videos with TensorFlow 2.x
Object detection is one of the areas in Deep Learning where much progress has been made. Using a variety of...
Getting started with PyTorch
When you want to build a deep learning model these days, there are two machine learning libraries that you must...
Using SELU with TensorFlow and Keras
Neural networks thrive on nonlinear data only when nonlinear activation functions are used. The Rectified Linear Unit, or RELU, is...
Bidirectional LSTMs with TensorFlow and Keras
Long Short-Term Memory networks or LSTMs are Neural Networks that are used in a variety of tasks. Used in Natural...
Build an LSTM Model with TensorFlow and Keras
Long Short-Term Memory (LSTM) based neural networks have played an important role in the field of Natural Language Processing. In...
ALBERT explained: A Lite BERT
Transformer models like GPT-3 and BERT have been really prominent in today’s Natural Language Processing landscape. They have built upon...
DALL·E: OpenAI GPT-3 model can draw pictures based on text
In 2020, the GPT-3 model created by OpenAI created big headlines: it was capable of generating text that could not...
Intuitive Introduction to BERT
Transformers are taking the world of NLP by storm. After being introduced in Vaswani et al.’s Attention is all you...
Intuitive Introduction to OpenAI GPT
Natural Language Processing is one of the fields where Machine Learning has really boosted progress in the past few years....
Differences between Autoregressive, Autoencoding and Sequence-to-Sequence Models in Machine Learning
Transformers have changed the application of Machine Learning in Natural Language Processing. They have replaced LSTMs as state-of-the-art (SOTA) approaches...
