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 of knowledge of machine learning.
Machine learning is getting used today in many different domains and some of them are:
1. Fraud detection
2. Web search
3. Text mining
4. Recommendation systems
5. Network intrusions etc
Importance of Machine Learning:
The use of Machine Learning has gone through to a different level where it has been used in different areas, some of them are:
1. Enhance their shopping experience
2. Enhancing the security at border crossing
3. Enhancing the decision-making system
1. Google Cloud Platform Fundamentals: Big Data & Machine Learning
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.
2. Data engineering on Google Cloud platform
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.
3. Heroku Machine Learning with PredictionIO
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.
4. Fairseq: putting in a CNN-based AI system
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.
5. Apache SystemML for Machine Learning
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.
6. Facebook NMT: putting in a neural AI system
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 apply required to implement a live Fairseq based mostly AI resolution.
7. Go Learn
Go Learn is one of the machine learning libraries that is available for “GO”. It is a fully featured, customizable package for Go developers.
8. AI in Automotive
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.
>> NUPIC stands for Numenta Platform for Intelligent Computing:
>> This is a brain inspired machine intelligence platform.
>> NUPIC is based on HTM machine learning algorithms. HTM stands for Hierarchical Temporal Memory.
>> NUPIC is an attempt to model the neocortex.
>> It focuses on storing recalling spatial patterns
>> This method or process is well suited for anomaly detection pattern.
>> The pattern is one of the projects that is developed on Machine Learning concepts.
>> It is a python based web mining tool kit.
>> It is associated with Computational Linguistics and Psycholinguistics (CLips)
>> This tool is capable of taking up tasks like scraping, machine learning, natural language processing, data visualization and network analysis.
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 take 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 caliber of Machine Learning and will benefit both the common man and at the same time help the businesses to grow exponentially.
If you feel that any other points that are worth mentioning then please do key in your suggestions in the Comments section below.
Happy Machine Learning!!
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