During the christmas vacation of 2015, I got a motivational boost again and decided try out Kaggle. So I spent quite some time experimenting with various algorithms for their Homesite Quote Conversion, Otto Group Product Classification and Bike Sharing Demand contests. The main takeaway from this was the experience of iteratively improving the results by experimenting with the algorithms and the data. I learned to trust my logic when doing machine learning. If tweaking a parameter or engineering a new feature seems like a good idea logically, it's quite likely that it actually will help.

Find the best Artificial Intelligence online course (AI) to learn. Learning AI is very easy now. Know about Artificial intelligence course syllabus, formats and content. In recent years AI Artificial Intelligence has made significant improvements in future technology. Artificial intelligence is playing a big role in making from smart Games to Self driving cars.

Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so, but sometimes the classes are no longer in session so you have to wait a couple of months, so you have no access. I'm going to be adding more videos from public sources and replacing the online course videos over time. I like using university lectures.

SAP SE (NYSE: SAP) today announced three new courses delivered on the openSAP platform to guide users through the transformative effects experienced as a result of using iOS technology, machine learning and SAP S/4HANA to implement everyday business processes. These courses come in addition to the recent release of "Upgrade of Systems Based on SAP NetWeaver – Advanced Topics," which investigates the latest tools and features essential for SAP software system upgrades and maintenance. The new courses on openSAP will cover how the partnership between SAP and Apple is optimizing the use of iOS technology for end-to-end business processes. They also provide users an in-depth look at how machine learning is giving rise to new intelligent applications. SAP Fiori for iOS – An Introduction: The recent partnership forged between SAP and Apple will enable developers to build quickly their own native apps for Apple iOS devices.

SAP uncovered its machine learning arsenal at this week's TechEd event in Barcelona. In an approach that is similar to Microsoft's, it is infusing machine learning across its business applications and making services available to encourage partners to build the techniques into their HANA built applications. Wherever you look there appears to be a machine learning element. There is a newly developed SAP Machine Learning Platform which will be available to partners and developers next year. The new HANA 2 features analytics improvements with new processing engines for text, spatial, graph and streaming data, driven by newly added classification, association, time series and regression machine learning algorithms.

SAP SE (NYSE: SAP) today introduced three initiatives to make its business applications more intelligent and empower its ecosystem to build machine learning (ML) applications for customers. Spanning its own solutions, partner programs and educational offerings, these programs will help accelerate ML adoption across SAP's global customer base. This announcement was made at the SAP TechEd conference, being held November 8-10, 2016, in Barcelona. First, SAP has unveiled new intelligent business applications. A new solution, "brand intelligence," is supposed to analyze brand exposure in video and images by leveraging deep learning.

Udacity, the education platform focused on helping workers gain skills they need for great careers in tech, has partnered with IBM Watson, Didi Chuxing and Amazon Alexa to offer a new nanodegree in artificial intelligence, the companies announced today at the IBM World of Watson conference. IBM Watson is co-developing the curriculum of the course with Udacity. Chinese ride-hailing company Didi Chuxing intends to hire students who successfully complete the nanodegree, as does IBM. And Amazon Alexa is serving as an advisor to Udacity in developing the new AI nanodegree. According to Udacity's founder Sebastian Thrun, who previously started Google's innovation shop Google X and its self-driving car initiative, the new AI nanodegree will be for students who already have a level of mastery in software development.

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This is my multi-month study plan for going from mobile developer (self-taught, no CS degree) to machine learning engineer. My main goal was to find an approach to studying Machine Learning that is mainly hands-on and abstracts most of the math for the beginner. This approach is unconventional because it's the top-down and results-first approach designed for software engineers. Please, feel free to make any contributions you feel will make it better. I'm following this plan to prepare for my near future job: Machine learning engineer.

A major challenge in crowdsourcing evaluation tasks like labeling objects, grading assignments in online courses, etc., is that of eliciting truthful responses from agents in the absence of verifiability. In this paper, we propose new reward mechanisms for such settings that, unlike many previously studied mechanisms, impose minimal assumptions on the structure and knowledge of the underlying generating model, can account for heterogeneity in the agents' abilities, require no extraneous elicitation from them, and furthermore allow their beliefs to be (almost) arbitrary. These mechanisms have the simple and intuitive structure of an output agreement mechanism: an agent gets a reward if her evaluation matches that of her peer, but unlike the classic output agreement mechanism, this reward is not the same across evaluations, but is inversely proportional to an appropriately defined popularity index of each evaluation. The popularity indices are computed by leveraging the existence of a large number of similar tasks, which is a typical characteristic of these settings. Experiments performed on MTurk workers demonstrate higher efficacy (with a $p$-value of $0.02$) of these mechanisms in inducing truthful behavior compared to the state of the art.