Machine Learning

Case Study: Predicting the Onset of Diabetes Within Five Years (part 2 of 3)

Last Updated on August 22, 2019 This is a guest post by Igor Shvartser, a clever young student I have been coaching. This post is part 2 in a 3 part series on modeling the famous Pima Indians Diabetes dataset (update: download from here).  In Part 1 we defined the problem and looked at the dataset, describing observations from the patterns we noticed in the data. In this we will introduce the methodology, spot checking algorithms, and review initial results. Kick-start your […]

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Machine Learning

BigML Tutorial: Develop Your First Decision Tree and Make Predictions

Last Updated on June 7, 2016 BigML is a fresh new and interesting machine learning as a service company based out of Corvallis, Oregon, USA. In a previous post, we reviewed the BigML service, the key features and the ways in which you could use this service in your business, on you side project or to present to clients. In this tutorial we will walk through a step-by-step tutorial on developing a predictive model using the BigML platform and use […]

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Machine Learning

Introduction to Bayesian Networks with Jhonatan de Souza Oliveira

Last Updated on August 16, 2020 This post is a spotlight interview with Jhonatan de Souza Oliveira on the topic of Bayesian Networks. Could you please introduce yourself? My name is Jhonatan Oliveira and I am an undergraduate student in Electrical Engineering at the Federal University of Vicosa, Brazil. I have been interested in Artificial Intelligence since the beginning of college, when had my first adventure investigating and building a simple chatbot for a Symposium website. I also am a member of an […]

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Machine Learning

Case Study: Predicting the Onset of Diabetes Within Five Years (part 3 of 3)

Last Updated on August 22, 2019 This is a guest post by Igor Shvartser, a clever young student I have been coaching. This post is part 3 in a 3 part series on modeling the famous Pima Indians Diabetes dataset that will investigate improvements to the classification accuracy and present final results (update: download from here). In Part 1 we defined the problem and looked at the dataset, describing observations from the patterns we noticed in the data. In Part 2 we […]

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Machine Learning

Python Machine Learning Books

Last Updated on August 16, 2020 Python is a very popular language for machine learning. The machine learning libraries and frameworks in Python (especially around the SciPy stack) are maturing quickly. They may not be as feature rich as R, but they are robust enough for small to medium scale production implementation. If you are a Python programmer looking to get into machine learning or you are generally interested to get into machine learning via Python, then I want to […]

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Machine Learning

A Gentle Introduction to Scikit-Learn: A Python Machine Learning Library

Last Updated on August 16, 2020 If you are a Python programmer or you are looking for a robust library you can use to bring machine learning into a production system then a library that you will want to seriously consider is scikit-learn. In this post you will get an overview of the scikit-learn library and useful references of where you can learn more. Kick-start your project with my new book Machine Learning Mastery With Python, including step-by-step tutorials and […]

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Machine Learning

Bootstrapping Machine Learning: An Upcoming Book on Prediction APIs

Last Updated on June 7, 2016 I came across an upcoming book that might interest you. It is titled Bootstrapping Machine Learning by Louis Dorard, PhD. A 40-page sample is provided and I enjoyed it. I think the final book will be a valuable read. Cover of the upcoming book: Bootstrapping Machine Learning Louis takes the position that machine learning is commoditized to the point where if you are an application developer, you don’t need to learn machine learn ing algorithms, you only need to learn machine […]

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Machine Learning

The Data Analytics Handbook: Data Analysts and Data Scientists

Last Updated on June 7, 2016 What is the difference between a Data Analyst and a Data Scientist and what type of work do they do all day? These questions and questions like them are answered in the new free ebook The Data Analytics Handbook: Data Analysts and Data Scientists. Cover of the The Data Analytics Handbook: Data Analysts and Data Scientists The ebook was created by Brian Liou, Tristan Tao and Elizabeth Lin. Brian and Tristan are Computer Science + Statistics grads and run the blog statsguys. Although […]

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Machine Learning

How to Get Started with Machine Learning in Python

Last Updated on August 21, 2019 The Python conference PyCon2014 has held recently and the videos for the conference are online. I have been working my way through the interesting machine learning ones and will share a few on this over the coming weeks. A great talk if you are starting out in data science or machine learning in python was given by Melanie Warrick titled How to Get Started with Machine Learning. It’s about 25 minutes long. The abstract […]

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Machine Learning

IPython from the shell to a book with a single tool with Fernando Perez

Last Updated on August 15, 2020 If you get serious with data analysis and machine learning in python then you will make good use of IPython notebooks. In this post we will review some takeaway points made by Fernando Perez, the creator of IPython in a keynote presentation at SciPy 2013. The title of the talk was IPython: from the shell to a book with a single tool; the method behind the madness. Kick-start your project with my new book Machine […]

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