Dutch universities are seeing significant growth in the number of students who want to study artificial intelligence in the coming academic year. At some educational institutions, the number of applications doubled compared to the current academic year. Interest in related courses, like data science and business analytics, is also on the rise, NOS reports.

If you want to put machine learning to work in your organisation, you should really consider securing a place at one of the four all-day workshops we're running as part of MCubed before our early bird ticket offer expires in two weeks time. Oliver Zeigermann returns to take you through the basics of machine learning, before diving into neural networks and deep learning and working up to convolutional neural networks, all using TensorFlow and sklearn. To learn how to build basic models and crucially get them into production in the real world, join Terry McCann for his workshop on "From model to production using the cloud, Containers and Devops". As well as using Python to develop models, this highly interactive session will show how to exploit common technologies such as Azure, Docker and Kubernetes. For a holistic, soup to nuts introduction to machine learning, join Prof Mark White and Kate Kilgour.

A foundation in statistics is required to be effective as a machine learning practitioner. The book "All of Statistics" was written specifically to provide a foundation in probability and statistics for computer science undergraduates that may have an interest in data mining and machine learning. As such, it is often recommended as a book to machine learning practitioners interested in expanding their understanding of statistics. In this post, you will discover the book "All of Statistics", the topics it covers, and a reading list intended for machine learning practitioners. All of Statistics for Machine Learning Photo by Chris Sorge, some rights reserved.

Pulled from the web, here is a our collection of the best, free books on Data Science, Big Data, Data Mining, Machine Learning, Python, R, SQL, NoSQL and more. Let's use the Reddit API to grab news headlines and perform Sentiment Analysis Expanding on the previous article, we'll be looking at how to incorporate recent price behaviors into our strategy In this post, we'll walk through building linear regression models to predict housing prices resulting from economic activity.

The education ministry plans to establish a system that allows students at some 50 high schools to take university courses and earn credits, with the aim of developing human resources in view of expected advances in artificial intelligence technologies. Advanced differential equation, data mining and other subjects in the mathematics and science fields will be covered by the planned version of the advanced placement system, which is used in the United States and other countries, according to ministry officials. The ministry is set to choose at least one high school from each of Japan's 47 prefectures over the next decade or so for the program. The planned initiative was included in a report compiled by a ministry panel discussing education policies for coming generations. Through the system, the ministry hopes to allow highly motivated high school students with excellent academic performances to receive even higher levels of education after they advance to university.

Create ML is proof that Apple is committed to making it easier for you to use machine learning models in your apps. In this Create ML tutorial, you'll learn how Create ML speeds up the workflow for improving your model by improving your data while also flattening the learning curve by doing it all in the comfort of Xcode and Swift. You don't need to know how to write a compiler to use Swift, and you don't need to be able to write a new ML algorithm to use a classifier. With Create ML, you have no excuse not to get started! You'll start this Create ML tutorial with the spectacular Create ML party trick: You'll build an image classifier in a GUI, using images from the Kaggle Cats and Dogs Dataset. Then you'll compare this with the Turi Create example that uses the same dataset. As you'll see, Turi Create is more manual, but it's also more flexible and not at all mysterious!

The Internet contains various categories of materials, some of which can be used as educational resources. These educational resources can be retrieved for content creation for use in Adaptive eLearning Systems (AES). Adaptive eLearning is a branch of eLearning that provides educational materials and resources based on the learners' needs. The adaptive learning system is not limited to delivering materials in a personalised manner to the learner; it also adapts in terms of interaction with learners and maintains learners' preferences. Artificial Intelligence plays a key role in adaptive eLearning by providing a personalised learning experience.

Bagging Bootstrapping The Bagging Algorithm Why Bagging Works LAB: Bagging Models Data scientist is called as the sexiest job of the 21st century. They take an enormous mass of messy data points (unstructured and structured) and use their formidable skills in math, statistics, and programming to clean, massage and organize. But worry not we are here to the rescue and teach you how to be a data scientist, more importantly, upgrade your analytic skills to tackle any problem in the field of data science. Join us on "statinfer.com" for becoming a "scientist in data science" Our "Machine Learning" course is now available on Udemy https://www.udemy.com/machine-learnin... Facebook link:- (Visit our facebook page we are sharing data science videos) https://www.facebook.com/aboutanalytics/ Visit our official website to go deeper into data science topics.

My company Invector Labs is starting a series of regular webinars about advanced computer science, research and technology topics applied to enterprise software. On July 25th I will be presenting the first webinar in the series that tries to give an overview of the overwhelming ecosystem of artificial intelligence(AI) frameworks, tools and platforms. In 30 mins we are going to try to provide a taxonomy that might help you reason through the large variety of AI technologies in the enterprise. As a rule, we don't do any marketing pitches during the presentation, just a discussion about computer science and practical AI. If you follow this blog because of the artificial intelligence(AI) research content, that webinar is for you.

In this tutorial, we will demonstrate how to implement the state of the art End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF paper for Named Entity Recognition using Pytorch. The main aim of the tutorial is to make the audience comfortable with Pytorch using this tutorial and give a step-by-step walkthrough of the Bi-LSTM-CNN-CRF architecture for Named-Entity-Recognition.