In this article, we will be discussing the Top 10 projects where Machine Learning was involved in one or the other way.
Machine learning has become one of the mainstays of information technology over the past few decades. It is a new data analysis domain which is becoming popular to automate advanced analytical model building. By utilizing new algorithms that repeatedly updates from data, it permits computers to search out hidden patterns and insights from the data.
Due to the growing volumes and varieties of the available data, computational processing is cheaper and more powerful and thus the increasing demand for knowledge of machine learning.
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Machine learning is getting used today in many different domains and some of them are:
The use of Machine Learning has gone through to a different level where it has been used in different areas, some of them are:
Now let’s discuss the projects where Machine Learning got implemented in one way or the other:
Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud Platform and a detailed view of the data processing and machine learning capabilities. The improvement, flexibility, and power of big data solutions on Google Cloud Platform are displayed by this process.
Data engineering course covers structured, unstructured, and streaming knowledge. Through a mix of shows, demos, and active labs, participants will ascertain a way to style process systems, build end-to-end knowledge pipelines, analyze knowledge and perform machine learning.
PredictionIO is Associate in Nursing open supply Machine Learning Server designed on prime of the progressive open supply stack. This course is directed at developers and knowledge scientists United Nations agency wish to form automotive engines for any machine learning task.
PredictionIO is known as a general-purpose framework. This framework has a lot of templates engines which are widely used. Some of the popular template engines are used for classifications and recommendations. These engines are conducted with the help of REST API’s or SDK.
Facebook has created the Fairseq that is that the ASCII text file sequence-to-sequence learning toolkit for the employment in NMT. During this coaching, the way to use Fairseq and to hold out interpretation of sample content can be learned by the participant.
Apache SystemML could be a distributed and declarative machine learning platform. It implements automatic generation of hybrid runtime plans, to distributed computations on Apache Hadoop and Apache Spark.
In this coaching, the participant can learn the way to use Fair Seq to hold out the interpretation of sample content. By the top of this coaching, the participants can have the information and applications required to implement a live Fairseq based mostly AI resolution.
Go Learn is one of the machine learning libraries that is available for “GO”. It is a fully-featured, customizable package for Go developers.
This course covers Artificial Intelligence (emphasizing Machine Learning and Deep Learning) in the automotive business. It helps to work out that technology may be (potentially) employed in multiple things during an automobile.
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This project is well executed and has a lot of well-written documentation and explains the topics with considerable examples and at the same time provide unit tests wherever it is necessary.
In this article, we have talked about the importance of Machine Learning and their usage in everyday life. A number of projects have already been taken up by the organization where they are seeing a drastic improvement in terms of predictions and also in a stage where they can make a quality decision with utmost accuracy.
All this possible because of the use of Machine Learning. In future, we are going to witness the true calibre of Machine Learning and will benefit both the common man and at the same time help the businesses to grow exponentially.
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Ravindra Savaram is a Content Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.