INTRODUCTION


Tensorflow Tutorial: Part 1 – Introduction

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This series is excerpts from a Webinar tutorial series I have conducted as part of the United Network of Professionals. Many applications as of today have tensorflow embedded as part of their machine learning applications. Let's explore the tensorflow environment and how the flexible architecture makes implementation so easy. This means you can execute code locally in your laptop with a CPU of a GPU if you have one.


Watson IoT Presenting Cognitive Coffee

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IBM Watson Internet of Things 2,130 views Cognitive Manufacturing with Watson IoT - Duration: 4:15. IBM Watson Internet of Things 6,978 views Watson IoT: Presenting Cognitive Coffee - Duration: 4:56. IBM Watson Internet of Things 11,228 views IBM CIO Leadership Exchange - Cognitive IoT: Where Digital Meets Physical - Duration: 42:55. IBM Watson Internet of Things 721 views Your brain on video games Daphne Bavelier - Duration: 17:58.


Is Artificial Intelligence (AI) the New Sales Frontier?

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Tim can be contacted on Twitter @timothy_hughes where he has some 175,000 followers or tim@social-experts.net Digital Leadership Associates is an agency to help companies move to digital and social. We help you to achieve your key business goals through three unique programs; Social Strategy definition and implementation, Social Selling training and mentoring and Social Presence management. We will help you define a Social Media strategy and whole-business understanding of your social vision, we equip your sales team with the tools and knowledge to become skilled at Social Selling and we offer deliver partial/whole management of your social presence. DLA provides advice and guidance to companies, given by actual Social practitioners, that is people with actual experience in social media, social and digital transformations.


5 EBooks to Read Before Getting into A Machine Learning Career

@machinelearnbot

Note that, while there are numerous machine learning ebooks available for free online, including many which are very well-known, I have opted to move past these "regulars" and seek out lesser-known and more niche options for readers. The book has wide coverage of probabilistic machine learning, including discrete graphical models, Markov decision processes, latent variable models, Gaussian process, stochastic and deterministic inference, among others. The material is excellent for advanced undergraduate or introductory graduate course in graphical models, or probabilistic machine learning. One of these target audiences is university students(undergraduate or graduate) learning about machine learning, including those who are beginning a career in deep learning and artificial intelligence research.


Introduction to Machine Learning for Developers

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The two main types of machine learning algorithms are supervised and unsupervised learning. There are many types of supervised algorithms available, one of the most popular ones is the Naive Bayes model which is often a good starting point for developers since it's fairly easy to understand the underlying probabilistic model and easy to execute. Decision trees are also a predictive model and have two types of trees: regression (which take continuous values) and classification models (which take finite values) and use a divide and conquer strategy that recursively separates the data to generate the tree. Check out the rest of the blog for more resources on natural language processing and machine learning algorithms such as LDA for text classification or increasing the accuracy on a Nudity Detection algorithm and a beginners tutorial on using Scikit-learn to solve FizzBuzz.


An Introduction to Implementing Neural Networks using TensorFlow

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Starting with this article, I will write a series of articles on deep learning covering the popular Deep Learning libraries and their hands-on implementation. Fast forward to 2012, a deep neural network architecture won the ImageNet challenge, a prestigious challenge to recognise objects from natural scenes. Nodes in the graph represents mathematical operations, while graph edges represent multi-dimensional data arrays (aka tensors) communicated between them. Here we solve our deep learning practice problem – Identify the Digits.


Answer Set Programming: An Introduction to the Special Issue

AI Magazine

This editorial introduces answer set programming, a vibrant research area in computational knowledge representation and declarative programming. We give a brief overview of the articles that form this special issue on answer set programming and of the main topics they discuss.


Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2015

AI Magazine

This issue features expanded versions of articles selected from the 2015 AAAI Conference on Innovative Applications of Artificial Intelligence held in Austin, Texas. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.


Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

AI Magazine

This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.


INTRODUCTION xiii PREHISTORY 1

Classics (Collection 2)

Some techniques for proving correctness of programs which alter data structures. D.J.M.DAviEs and S.D.ISARD 325 18 The syntactic inference problem applied to biological systems.