Two of the top numerical platforms in Python that provide the basis for Deep Learning research and development are Theano and TensorFlow. Both are very powerful libraries, but both can be difficult to use directly for creating deep learning models. In this post, you will discover the Keras Python library that provides a clean and […]
The scikit-learn library is the premiere library for machine learning in Python. The online documentation is quite good but sometimes can feel fragmented or limited by narrow examples. In this post you will discover the book Scikit-Learn Cookbook by Trent Hauck that provides a desktop reference to supplement the online documentation and help you get […]
The scikit-learn library is one of the most popular platforms for everyday machine learning and data science. The reason is because it is built upon Python, a fully featured programming language. But how do you get started with machine learning with scikit-learn. Kevin Markham is a data science trainer who created a series of 9 […]
You do not need to be a Python developer to get started using the Python ecosystem for machine learning. As a developer who already knows how to program in one or more programming languages, you are able to pick up a new language like Python very quickly. You just need to know a few properties of the […]
Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can use directly to create Deep Learning models or wrapper libraries that greatly simplify the process. In this post you will discover the Theano […]
The Python ecosystem is growing and may become the dominant platform for machine learning. The primarily rationale for adopting Python for machine learning is because it is a general purpose programming language that you can use both for research and development and in production. In this post you will discover the Python ecosystem for machine learning. Let’s get started. […]
Machine learning algorithms are a very large part of machine learning. You have to understand how they work to make any progress in the field. In this post you will discover a 14-part machine learning algorithms mini course that you can follow to finally understand machine learning algorithms. We are going to cover a lot […]
There are a lot of machine learning algorithms and each algorithm is an island of research. You have to choose the level of detail that you study machine learning algorithms. There is a sweet spot if you are a developer interested in applied predictive modeling. This post describes that sweet spot and gives you a […]
Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers. In this post you will discover the AdaBoost Ensemble method for machine learning. After reading this post, you will know: What the boosting ensemble method is and generally how it works. How to learn to boost decision […]
Random Forest is one of the most popular and most powerful machine learning algorithms. It is a type of ensemble machine learning algorithm called Bootstrap Aggregation or bagging. In this post you will discover the Bagging ensemble algorithm and the Random Forest algorithm for predictive modeling. After reading this post you will know about: The […]
