This tutorial is a practical guide which helps you to create Neural Networks in Chainer. The focus is not on the architecture of the networks (more about Neural Network architectures is found in this post), but it is focused on creating a pipeline. We will take a simple classification problem as an example and create the pipeline for training and testing the network and how to evaluate the model.

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## Mastering Pandas

In this course, you will learn how to use the Python Pandas. After the course, you will be able to:

- Load and transform your data
- Visualizing data using line plots, scatter plots and histograms
- Merging and storing data

The course also includes more advanced topics, such as data parallelization and aggregation.

You can see all course content under “Curriculum” on Data Blogger Courses and the first three lessons are free. The first free lesson can be found here.

(more…) Read more## The Mathematics Behind: Polynomial Curve Fitting (MATLAB)

In the series “The Mathematics Behind” I will explain mathematical concepts behind commonly used technologies. In this post, I will explain the mathematics behind polynomial curve fitting MATLAB.

First of all, what is polynomial curve fitting and where is it used for? Suppose we are trading on a stock market. The stock price is going up and down (see the figure) and we want to discover patterns in the price chances if any exists. Polynomial curve fitting tries to fit a model (here: a polynomial) on the given datapoints as good as possible.

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