Data is rarely clean and often you can have corrupt or missing values. It is important to identify, mark and handle missing data when developing machine learning models in order to get the very best performance. In this post you will discover how to handle missing values in your machine learning data using Weka. How To Handle Missing Data For Machine Learning in Weka Photo by Peter Sitte, some rights reserved. The problem used for this example is the Pima Indians onset of diabetes dataset.

Deep learning is a fascinating field of study and the techniques are achieving world class results in a range of challenging machine learning problems. Which library should you use and which techniques should you focus on? In this post you will discover a 14-part crash course into deep learning in Python with the easy to use and powerful Keras library. This mini-course is intended for python machine learning practitioners that are already comfortable with scikit-learn on the SciPy ecosystem for machine learning. Applied Deep Learning in Python Mini-Course Photo by darkday, some rights reserved. Before we get started, let's make sure you are in the right place.

This has been one of the most intriguing questions in science fiction and philosophy since the advent of machines. With modern technology, such questions are no longer bound to creative conjecture. Machine learning is all around us. From deciding which movie you might want to watch next on Netflix to predicting stock market trends, machine learning has a profound impact on how data is understood in the modern era. This tutorial aims to give you an accessible introduction on how to use machine learning techniques for your projects and data sets. In just 20 minutes, you will learn how to use Python to apply different machine learning techniques -- from decision trees to deep neural networks -- to a sample data set.

Because we'll need something tasty to swill when our robot overlords finally come into their full artificial intelligence, a company in the UK is attempting to figure out if robots can help humans brew a better beer. While there won't be robots stirring batches of wort or sorting hops, artificial intelligence will play a big part in London-based firm IntelligentX's plan to brew beer, CNET reports. Here's how it'd work: consumers would try one of the company's four beers -- Amber AI, Black AI, Golden AI and Pale AI ---- and then weigh in via Facebook chat bot on the experience. That feedback will be fed to an algorithm called Automated Brewing Intelligence, or ABI, which will use the information to make changes to the next batch. Reinforcement learning and a process called bayesian decision making will teach the AI about the brewing experience.

If free books on machine learning aren't enough for you, Open Source Society University has a free online course on Data Science. I wonder how their football team will do this Fall?

Celestion loudspeakers have powered the performances of many noted guitar and bass players, including legends such as Jimi Hendrix. Deciding whether a loudspeaker is good enough for professional musicians is a lengthy and painstaking process. Each speaker has its own unique sound based on a combination of sonic characteristics, such as midrange character and brightness. Evaluating a musical instrument loudspeaker involves subjective judgement about whether it generates a "good" sound. Only engineers with years of experience can reliably make that decision, and then only after repeated listening to a single loudspeaker and comparing the sounds it produces with those produced by a reference speaker.

Personalizing the News Feed: A Large-Scale Recommendation Problem Personalization is a key component in ensuring user satisfaction, and at Yahoo, personalization is at the heart of several user-facing products. This talk will focus on how Yahoo built one of the largest news recommendation engines in the world: the Yahoo stream, which personalizes the news feed for several hundreds of millions of users on millions of content items. Beyond the scale, the success of the news feed also depends on whether it is able to engage the user long term. In this session, Yahoo's director of research will present the challenges and issues in designing an engaging stream, and attendees will also learn how to cope with sparsity of explicit feedback, how user behavior changes with context of the device, how to build machine learned models for each user, and the metric that allows Yahoo to optimize for long term user-engagement.

Being able to make near-real-time decisions becomes increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning applications? The answer is TensorFlow, a new open source machine learning library from Google that they use in their own successful products like Search, Maps, YouTube, Translate, and Photos. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms.

Hell, Microsoft issued an Education Edition of the popular PC game earlier this year targeted at use in a classroom setting. Turns out the game could also prove a useful tool for helping artificial intelligence be more, well, intelligent. Back in March, Microsoft Research showcased the work it was doing with Project Malmo, a platform designed to leverage Minecraft as a means of helping improve AI problem solving, using machines to accomplish tasks and create items in the blocky game. Now the company is bringing Malmo to the GitHub-using masses, courtesy of an open-source license in a private preview. Katja Hoffman of MS's Cambridge, UK lab highlighted the key of teaching AI fundamental connections that go build simple pattern recognition.

Learn how to build a personal chatbot for Facebook Messenger. I have created this step by step guide so you can create your own Facebook Messenger bot without coding. Facebook Messenger has a growing audience of 900 mln. It is an awesome opportunity to showcase your work and promote your services, automate conversations and build out your personal brand. By the end of the course you will be launch and promote your personal bot.