In data science, when trying to discover the trends and patterns inside of data, you may run into many different scenarios. For example, you could run into a situation where the data is not linear, you have more than one…
Creating different machine learning models in Keras becomes super easy once we understand the fundamentals. Getting the correct output shape starts with correctly defining the right input shape for your deep learning models. If you mess this up, you’ll spend…
Deep learning can be tricky, but we have some APIs that help us create wonderful models that can quickly converge to a great solution. The Keras API used for neural networks has risen in popularity for modeling with TensorFlow. Keras…
Topic modeling is a dense but gratifying subject. Knowing how to put your text into specific topics is crucial to understanding the different genres within your text. Utilizing topic modeling also allows you to quickly ingest ideas from your text…
Keras, while powerful, does have many different hyperparameters to choose from. Messing up steps_per_epoch while modeling with the .fit method in Keras can create a ton of problems. This guide will show you what steps_per_epoch does, how to figure out…
The Dense layer is a critical component in Machine Learning. While the most straightforward layer, the dense layer is still vital in any neural network design and is one of the most commonly used layers. Below we will be breaking…
