This week you'll learn about the Introduction to Recurrent Neural Networks with Keras and TensorFlow.

Image

Our brains are magical creations of this world. Imagine being able to perceive everything around you visually, through touch, sound, and taste, all simultaneously. Using today's computational wonders, we can only hope to create something close to what our brain can accomplish. 

The ease at which our brain understands language is outrageous. Unfortunately, computers and algorithms do not have that capability. For years, we have continually tried to develop algorithms capable of learning language in a manner at par with humans. 

Paradigm-based algorithms, statistical approaches, and embeddings were some of how researchers used to try for good results. But one thing wasn't taken into account: the sequence of data. 

The idea behind keeping the sequential nature of data alive lay in the fact that the sequential structure helped better define the meaning of words and their context.  

That brings us to today's blog, Introduction to Recurrent Neural Networks with Keras and TensorFlow. Finally, an algorithm that provides a solution for keeping the information in sequences alive. 

The big picture: Recurrent Neural Networks (RNNs) are a type of artificial neural network which aims to define a cyclic network that can help keep the information from previous states in a sequence alive. 

How it works: An RNN cell takes in the current input and a hidden state (from the previous state) to compute the current state output. This way, we are taking into account information of the prior state. 

Our thoughts: As an introduction to sequence modeling, this is a great way to familiarize yourself with the intricacies of dealing with sequence data and modeling. 

Yes, but: RNNs are a great introduction, but there have been several upgrades to sequence modeling approaches. 

Stay smart: Having a strong foundation in recurrent neural networks will give readers a better understanding of the upcoming blogs on sequence modeling.

Click here to read the full tutorial

Solve Your CV/DL problem this week (or weekend) with our Working Code

You can instantly access all of the code for Introduction to Recurrent Neural Networks with Keras and TensorFlow by joining PyImageSearch University. Get working code to

  1. Finish your project this weekend with our code
  2. Solve your thorniest coding problems at work this week to show off your expertise
  3. Publish groundbreaking research without multiple tries at coding the hard parts

Guaranteed Results: If you haven't accomplished your CV/DL goals, let us know within 30 days of purchase and get a full refund.

I want the code

Note: You may have missed this, but last Wednesday, we published a new post on Computer Vision and Deep Learning for Banking and Finance.



The PyImageSearch Team