Time Series Forecasting

Time Series Forecasting

Time Series Forecasting is an important area of Machine Learning that is often Neglected. Time Series Forecasting uses different Technologies like Machine learning, Artificial neural networks, Support vector machines, Fuzzy logic, Gaussian processes, Hidden Markov models What is Time Series? A time series is a sequence of measurements done over time, usually obtained at equally spaced intervals, be it daily, monthly, quarterly or yearly. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other

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Machine Learning and Pattern Recognition

Machine Learning and Pattern Recognition

Machine Learning and Pattern Recognition Machine Learning and Pattern Recognition : In a very simple language, Pattern Recognition is a type of problem while Machine Learning is a type of solution. Pattern recognition is closely related to artificial intelligence and machine learning. Pattern Recognition is an engineering application of Machine Learning. Machine learning deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions whereas Pattern recognition is the recognition of

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Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence Difference between Machine Learning and Artificial Intelligence : Okay Google! What’s Up? Could you play my favourite track or Book a Cab from Palace Road to MG Road. Alexa, What time it is? Wake me up at 5AM. Could you please tell my tomorrow meetings. These are the perfect combination of Machine Learning and Artificial Intelligence. Machine learning: Machine learning is a method of data analysis that automates analytical model building. Machine learning is a

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Big Data and Artificial Intelligence

Big Data vs. Artificial Intelligence

Big Data vs. Artificial Intelligence – Introduction: Big Data: The growth of the world is impulsive in all ways, likewise the data. Data size across the world is huge, so technically increase in the data constitute the name Big Data. The time of spread sheet is over, A google search, Passport scan,  a barcode reading in supermarket, your online shopping history, An EKG reading, CCTV footage, A photo of a sandwich, a voice message, A tweet, all of this contains

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Pig Case Study – Complain Raised by different Software Companies.

pig

Pig Case Study : Problem Statement: To build a script which produces a report listing each Company & State and number of complaints raised by them. We have a data set of complaints (incidents or trouble tickets) of a software system raised by different companies. The details of the fields (i.e. data dictionary) of each record is in below format: Date received = dtr:chararray, Product = prd:chararray, Sub-product =  sprd:chararray, Issue = iss:chararray, Sub-issue = siss:chararray, Company public response =

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Apache Hadoop Vs Apache Spark

Apache Hadoop

What is Big Data? What size of Data is considered to be big and will be termed as Big Data?  We have many relative assumptions for the term Big Data. It is possible that, the amount of data say 50 terabytes can be considered as Big Data for Start-up’s but it may not be Big Data for the companies like Google and Facebook. It is because they have infrastructure to store and process this vast amount of data. When data

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Everything is on Internet! The Internet has a lot of Data! Therefore, everything is Big Data!!

What is Data Science

What is Data Science? Data Science is the art and science of extracting actionable insight from raw data. Put simply, Data Science is an umbrella term for techniques used when trying to extract insights and information from data. Data Science uses automated methods to analyze huge amount of data and extract knowledge from them in various forms either structured or unstructured. Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be

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Machine Learning vs Deep Learning: Here’s what you must know!

Machine Learning vs Deep Learning

Artificial Intelligence (AI) and Machine Learning (ML) are two words casually thrown around in everyday conversations, be it at offices, institutes or technology meetups. Artificial Intelligence is said to be the future enabled by Machine Learning. Now, Artificial Intelligence is defined as “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” Putting it simply means making machines smarter to replicate human tasks, and

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What is Data Analytics?

Data Analytics

Big Data Analytics as a buzzword has generated much hype in recent times. It is said to be the answer to any marketer’s woes, the way to generate highly focused, customized advertisements and marketing strategies that give the consumers what they want. But what exactly is big data? As the name implies – it is data, which is big in volume. Simply put, it is data that is too large to be processed using traditional data processing mechanisms. With the

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Machine Learning is the future: Here’s everything you must know

Machine Learning

What is Machine Learning (ML)? This is arguably the most exciting times in the world of technology, owing to deeper penetration of mobile phones, Internet and newer emerging technologies. Computers have changed the world as we see it. They are faster than us when it comes to solving mathematical problems. On the other hand, the intelligent human mind cannot really process data at the speeds which a computer can. But, computers are not ‘intelligent’ as they can’t do anything themselves.

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