A lot of this confusion surfaces around the scope of machine learning. While there is a lot of hype around deep learning, it is just a subfield of machine learning. The simplest definition one can give is: if you are using statistics to solve a problem you can reasonably argue you are using machine learning to solve your problem.
When you are starting off in Machine Learning you will play around with a lot of static datasets. This is normally in the form of…
Keras is a favorite tool among many in Machine Learning. TensorFlow is even replacing their high level API with Keras come TensorFlow version 2. For those new to Keras. Keras is called a “front-end” api for machine learning. Using Keras you can swap out the “backend” between many frameworks in eluding TensorFlow, Theano, or CNTK officially.
We are going to dive into the convolution layer in this post. In particular we are going to dive into how filters work. Before we jump into this let us look at how data goes into a convolutional layer.