How machine learning can improve software development itself


The activities of many globally active IT corporations prove that machine learning will be high on their lists. Be it Google, IBM or Microsoft – all of them have made machine learning an important component of their business strategies. In addition, the tech giants have been recruiting entire competence teams and acquiring machine learning and AI startups. While IT, automotive, telecommunications and media are among the pioneers of this development, more traditional industries such as the chemicals sector, logistics/transportation and pharmaceuticals are already awaiting their turn. This makes me wonder whether machine learning can offer genuine value to the field of software development itself.

Machine Learning: An Introduction to Supervised and Unsupervised Learning Algorithms


The phrase "Machine Learning" refers to the automatic detection of meaningful data by computing systems. In the last few decades, it has become a common tool in almost any task that needs to understand data from large data sets. One of the biggest application of machine learning technology is the search engine. Search engines learn how to provide the best results based on historic, trending, and relative data sets. When you look at anti-spam software, it learns how to filter email messages.

How AlphaGo Works


The slides go through the implementation details of Google Deepmind's AlphaGo, a computer Go AI that defeated the European champion. The slides are targeted for beginners in the machine learning area.

Is Your Data Ready for Machine Learning? VMware Radius


Artificial intelligence is changing the world more rapidly than anyone could have predicted a few years ago. The explosion in available data, coupled with low-cost computing power and dramatic advances in AI capabilities, will enable organizations to optimize their operations, personalize their products, and anticipate future demand.

Amateur trying to get started with MachineLearning • /r/MachineLearning


I've been following this subreddit for some time, as well as read articles and watched videos on machine learning trying to get started with ML. I understand the basic concepts and have some very basic knowledge of python. The reason for this is that I believe I could apply machine learning to a work project I'm working on which involves image analysis. The problem is that I just can't seem to really get the hang ofsome of the practical basics, as I'm quite new to programming. What I'm trying to accomplish is basically an algorithm which automatically identifies certain objects in larger images, and returns the amount of detected items.