### 1. Keras for Beginners: Building Your First Neural Network

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A beginner-friendly guide on using Keras to implement a simple Neural Network in Python.

Keras is a simple-to-use but powerful deep learning library for Python. This 3-post series, written for beginners, provides a simple way for anyone to get started solving real machine learning problems. We’ll start with an introduction to **classic Neural Networks** for complete beginners before delving into two popular variants: **Recurrent Neural Networks** (RNNs) and **Convolutional Neural Networks** (CNNs).

For each of each these types of networks, we’ll:

- Introduce a (simple) real-world problem
- Preprocess the dataset
- Build a model for the problem
- Train and test the model
- Brainstorm ideas to keep improving the model

At the end of each post, you’ll have the full code to accomplish everything listed above.

**This series requires ZERO prior experience with Keras or Tensorflow.** However, background in the following topics may be helpful:

**Neural Networks**in general (how do they work, what are they for?). I recommend my Neural Networks from Scratch series to get started here.**Python**- basic familiarity with the language will help you move through the series faster.- Experience with other deep-learning libraries, which will help you ramp up faster on Keras.

Without further ado:

| UPDATED

A beginner-friendly guide on using Keras to implement a simple Neural Network in Python.

| UPDATED

A beginner-friendly guide on using Keras to implement a simple Convolutional Neural Network (CNN) in Python.

A beginner-friendly guide on using Keras to implement a simple Recurrent Neural Network (RNN) in Python.

Still eager to learn? Some more things you can do include:

- Apply neural networks to Visual Question Answering (VQA), an interesting Computer Vision problem.
- Try your hand at using Neural Networks to approach a Kaggle data science competition.
- Take one of many good Neural Networks courses on Coursera.

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