Closing the Gap Between Data Scientists and Domain Experts for Successful Machine Learning Application
This paper identifies a gap in the application of machine learning in the industry, especially petroleum. Recent development has led to massive employment of data scientists who know little about the problem domain. It is recommended that data scientists work closely with domain experts to build robust solutions rather than working in isolation.
Analytics and Emails – Spam
The 1990s marked the beginning of internet with Hotmail being the first web-based email provider. Standards such as sender authentication, whitelisting, etc. were unknown. Marketers exploited this opportunity. The strategy was 'just send it‘. As a result, our inboxes get flooded with junk emails every day.
Machine Learning with Python by Ajit Singh
Machine learning can be described as a form of statistical analysis, often even utilizing well-known and familiar techniques, that has bit of a different focus than traditional analytical practice in applied disciplines. The key notion is that flexible, automatic approaches are used to detect patterns within the data, with a primary focus on making predictions on future data.
7 Facts Everyone Should Know About Data Science
You should have a clear concept and theory behind all the statistical methods and programming. To master statistics, one can consider joining Data Science Training in Noida.
International Data Science Awards Live and Entry Pages Open
The entry pages for the International Data Science Awards are now live and entries are being accepted. The awards were launched at the AI & Big Data Expo held at Olympia, London on 25 April. Entry pages will remain open until September with judging taking place in October.
Machine Learning : An Overview
The machine learning being done today is generally based on some sort of observations or data, such as examples (the most common case), direct experience, or instruction. In general, machine learning is about learning to do better in the future, based on what was experienced in the past.
Graph Analytics and Big Data
Graph analytics, which is an analytics alternative that uses an abstraction called a graph model. The simplicity of this model allows for rapidly absorbing and connecting large volumes of data from many sources in ways that finesse limitations of the source structures (or lack thereof, of course). Graph analytics is an alternative to the traditional data warehouse model as a framework for absorbing both structured and unstructured data from various sources to enable analysts to probe the data in an undirected manner. Big data analytics systems should enable a platform that can support different analytics techniques that can be adapted in ways that help solve a variety of challenging problems. This suggests that these systems are high performance, elastic distributed data environments that enable the use of creative algorithms to exploit variant modes of data management in ways that differ from the traditional batch-oriented approach of traditional approaches to data warehousing.
Big Data Analytics and Predicting Election Results
The best way to predict the future is to study past behavior. This is the underlying idea behind Big Data Analytics. The 2008 Obama election campaign was one of the first to take advantage of data-driven methods in the race to an elected office. The Obama campaign had a data analytics team of 100 people. This shows how deeply data analytics impacts the world.
Architecture of Data Lake
Data can be traced from various consumer sources. Managing data is one of the most serious challenges faced by organizations today. Organizations are adopting the data lake models because lakes provide raw data that users can use for data experimentation and advanced analytics. A data lake could be a merging point of new and historic data, thereby drawing correlations across all data using advanced analytics. A data lake can support the self-service data practices.
Big Data: The next frontier for advance, competition, and efficiency
Nowadays organisations are starting to realise the importance of using more data in order to support decision for their strategies. The size of data in the world is growing day by day. Data is growing because of vast use of internet, smart phone and social network. Big data is a collection of data sets which is very large in size as well as complex. Generally size of the data is Petabyte and Exabyte. Traditional database systems are not able to capture, store and analyse this large amount of data. As the internet is growing, the amount of big data continues to grow. Big data analytics provide new ways for businesses and government to analyse unstructured data. Nowadays, big data is one of the most talked about topic in the IT industry. It is going to play an important role in the future. Big data changes the way that data is managed and used. Some of the applications are in areas such as healthcare, defence, traffic management, banking, agriculture, retail, education and so on. Organisations are becoming more flexible and more open. New types of data will give new challenges as well.
Nonparametric Statistical Test Approaches in Genetics Data
The biggest challenge of genetic research lies in significant and intellectual analysis of the large and complex data sets generated by the cutting edge techniques like massively parallel DNA sequencing and genome wide analysis. Statistical analyses are the most important of such experimental data. When the data are not normally distributed and using non numerical (rank, categorical) data then use the nonparametric test for exact result of research hypothesis. Order statistics are among the most fundamental tools in non-parametric statistics and inference. Non parametric test does not depend upon parameters of the population from which the samples are drawn, no strict assumption about the distribution of the population. Nonparametric tests are known as distribution free test also because their assumptions are less and weaker than those connected with parametric test. Nonparametric test does not follow probability distribution. To analyze microarrays and genomics data several non-parametric statistical techniques are used like Wilcoxon’s signed rank test (pre-post group),Mann-Whitney U test (two groups) or Kruskal-Wallis test (two or more groups).Importance of this paper is to look at the non-parametric test how to use in genetic research and provide the understanding of these test
Thank you all for your support and cooperation.Regards,Ajit SinghREAD MORE
Its now time to start thinking about the project you will enter into the International Data Science Awards. The Support of the Chartered Institute of Public Relations will really help to raise the profile of the awards and generate interest in the participantsREAD MORE
I tried at my best to bring the retail coffee business across all of you.Request you all to please share your valuable and experienced suggestions......Regards,Ajit SinghREAD MORE
Nice initiative and hope for the best......READ MORE
Excellent coverage on HR Operations along with AI........READ MORE
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Congratulations......Excellent contributions from the each & every participants.READ MORE
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I have written this article to bring the focus on freelancing in Data Science as well as the importance of Data Science Foundation for it's facilitation for the Data Scientists......Request you all to share your valueable suggestions for this article....READ MORE
Request you all to please share your valuable suggestions, if there is any.Regards,Ajit SinghREAD MORE
Request you all to please provide your valuable suggestions......Regards,Ajit SinghREAD MORE
How is Artificial Intelligence (AI) going to change the world? Will it free us from the burden of having to work so we can live in a cultured utopia, or will it enslave us all like The Matrix would have us believe?READ MORE
Dr Stephen Simpson and Hugh Shields, founders of UK-based corporate performance consultancy Alpha Fortius, advise on how to survive and thrive in the new world of AIREAD MORE
According to a report published last year by Dresner Advisory Services, big data adoption in enterprise steeply climbed from 17% in 2015 to 59% in 2018.READ MORE
Futurists, demographers, and marketers have yet to agree on the specifics of what defines the next wave of humanity to follow Generation Z.READ MORE
You can delete voice recordings so Amazon can't listen to your conversations with Alexa anymore, but text records are a different story.READ MORE
Ingress is not an easy game to understand or play. Unlike Niantic’s later hit Pokémon Go, which has a cheerful, casual tone, Ingress is a sci-fi tale about humanity on the brink of destruction. The discovery of a powerful force called Exotic Matter (XM) divides players – called agents – into the Resistance and the Enlightened.READ MORE
At Google I/O, Google launched new capabilities for the machine learning SDK available on Firebase.READ MORE
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) has created a new deep learning model that can predict from a mammogram if a patient is likely to develop breast cancer in the future.READ MORE
A new report from Reuters reveals that contract workers are looking at private posts on Facebook and Instagram in order to label them for AI systems.READ MORE
The TL DR is that AI is the science of building computers that can solve problems the way humans do. But there's much (much) more to it than that.READ MORE
From wearable health and training devices to goal line assistance in football, technology has been invading the sporting field for some years. Whether by helping the athletes up their game, catching rule infringements, or improving safety, this tech has largely all fallen within the same broad aim of improving game play.READ MORE
With technology becoming more affordable, what are the opportunities for immersive technologies – virtual, augmented and mixed reality – for engineering and construction?READ MORE
Labor will build an artificial intelligence centre of excellence to help prevent more "robodebt" disasters happening in government and business.READ MORE
Collecting image scans of tumours from patients with lung cancer and running them through advanced artificial intelligence (AI) models returns improved predictions of predicted patient response and survival outcomes than standard clinical checks, a study has found.READ MORE
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