In this post we will talk about the Kepler dataset from Kaggle competitions and use it to build an exoplanet detection model using TensorFlow's prebuilt estimator for gradient boosting trees known as the BoostedTreesClassifier.

Detecting exoplanets in outer space

For the project explained in this post, we use the Kepler labeled time series data from Kaggle. This dataset is derived mainly from the Campaign 3 observations of the mission by…

Did you ever wonder why linear regression plays an important role in statistics and machine learning? It is witnessed that linear regression is one of the most commonly and well-understood algorithms. 

Regression is a statistical method for calculating relationships among variables. It is one of the most popular and simplest regression…

In order to be a highly efficient, flexible, and production-ready library, TensorFlow uses dataflow graphs to represent computation in terms of the relationships between individual operations. Dataflow is a programming model widely used in parallel computing and, in a dataflow graph, the nodes represent units of computation while the edges represent the data consumed or produced by a computation unit.

This post is taken from the book…

Keras [Chollet, François. "Keras (2015)." (2017)] is a popular deep learning library with over 250,000 developers at the time of writing, and over 600 active contributors. This library is dedicated to accelerating the implementation of deep learning models. This makes Keras ideal when we want to be practical and hands-on.

Keras enables us to build and train models efficiently. In the library, layers are connected…