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Machine Learning

What is Machine Learning?

     Machine learning is the ability of computer systems to constantly learn and improve. It is a subset of computer science that evolved through the study of artificial inteligence. More specifically, it is known as the field of study that allows computers and systems to learn automatically, without human intervention or assistance and adjust actions accordingly.

    Machine learning focuses on the development of computer programs and algorithms that can access data and learn for themselves. These algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. 


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Μachine Learning Applications

Microsoft's Solutions for Machine Learning.

     Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel. The classic version of Azure Machine Learning Studio gives you an interactive, visual workspace to easily build, test, and iterate on a predictive analysis model.You drag-and-drop datasets and analysis modules onto an interactive canvas, connecting them together to form an experiment, which you run in Machine Learning Studio (classic). To iterate on your model design, you edit the experiment, save a copy if desired, and run it again. When you're ready, you can convert your training experiment to a predictive experiment, and then publish it as a web service so that your model can be accessed by others.  

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SAP's solution for Machine Learning.

     SAP Leonardo is a digital innovation system that utilizes Machine Learning technology.The goal of SAP Leonardo is to help you “innovate at scale to confidently redefine your business.” Unlock knowledge from structured and unstructured data using machine learning technology. With the help of easy-to-use application programming interfaces (APIs), you can use the foundation to enable intelligent enterprise applications.

     • Cloud deployment

     • Ready-to-use machine learning services

     • Customizable machine learning services

     • Ability to deploy your own models 

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 IBM 's solutions for Machine Learning.

     Machine learning is a form of AI that enables a system to learn from data rather than through explicit programming. However, machine learning is not a simple process. As the algorithms ingest training data, it is then possible to produce more precise models based on that data. A machine-learning model is the output generated when you train your machine-learning algorithm with data. After training, when you provide a model with an input, you will be given an output. For example, a predictive algorithm will create a predictive model. Then, when you provide the predictive model with data, you will receive a prediction based on the data that trained the model.


The 4 categories of machine learning are:

     •Supervised learning

     •Unsupervised learning

     •Reinforcement learning

     •Deep learning

IBM's products that utilize Machine Learning are Watson Studio, IBM Machine Learning for z/OS,  IBM SPSS® Modeler και IBM Watson Explorer.

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Google's solution for Machine Learning.

     Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs. It relies on Google’s state-of-the-art transfer learning and neural architecture search technology.

Some of their key feautures are:

     • State-of-the-art performance

     • High-quality training data

     • Evaluation, improvement, and deployment of models based on your own data

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