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WHITEPAPERS

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LATEST DISCUSSION

Very informative course by Cisco;

05 April 2021 | Prateek Agarwal

Dear All,Recently I have completed a course on the Internet of Things (IoT) by Cisco.Cisco Networking Academy transforms the lives of learners, educators, and communities through the power of technology, education, and career opportunities. Available to anyone, anywhere. I found it very useful.

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DEEP LEARNING: FIGHTING COVID-19 WITH NEURAL NETWORKS;

03 March 2021 | Balakrishnan Subramanian

Thanks for the article, nicely explained along with covering the basic aspects.Also I was working on the dataset (from kaggle) on to predict covid through X-Rays, but seems using CNN or others not getting good score or prediction.After reading the article, seems got more details, and will try to implement in the EDA part and then train the model. Hope this should increase the prediction probability.

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Understanding Buzzwords in Data Science;

24 December 2020 | Mayank Tripathi

Brilliant work.Very well-written article. Yes, I have heard a lot about this "buzzword" around me and thinking it is the only "buzzword" you need to adopt and survive in the IT industry.Is it true?

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Piecewise hazard model for under-five child mortality;

06 December 2020 | Rakesh Saroj

The application of piecewise hazard model in mortality data becomes more useful in survival methods. This method is used to find the number and location cut points and to estimate the hazard model. The objective of this paper is to illustrate the piecewise constant hazard model and to find significant factors for under-five child mortality.

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Aurora Serverless Data Security and its Deployment;

17 November 2020 | Balakrishnan Subramanian

In this article, Data Security acts as an important segment. This consists of certain standard levels and various technologies that are used for data protection. This helps to secure data from accidental destruction and altering disclosures. Overall, in this article Aurora Serverless data security is majorly pointed. The AWS creates Aurora, which is nothing but a cloud-native execution of RDBMS. Finally, the implementation of Aurora is “serverless”.

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Machine learning tool scans lung X-rays to predict heart fai;

05 October 2020 | Stefan Stoyanov

One of the ways physicians can gain some forewarning of impending heart failure is through the detection of excess fluid in the lungs, and MIT researchers have developed a new machine learning tool that could offer them a helping hand. The algorithm is able to detect severe cases of this condition with a high level of accuracy, and the researchers behind it are hopeful it could be adapted to assist with the management of other conditions, too. Learn more here: https://bit.ly/2HQaKR4

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Data set for content-based package selection in the telecom;

26 September 2020 | Thisal Avishka Wijayasekara

I have a Data Cloud Lab and Github too, Ready to contribute someone like you. please send me your resume at darrajit@gmail.com. I will find out your solution. Thank you

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Real Time Data Analytics: Mitigating the Risks and the Challenges;

20 September 2020 | Michael Baron

Agree, with the time researchers has found various tools and techniques that today one can do real time data analysis, but again it depends on the person, how (s)he will be using the tools and techniques with respect to the creativity. As to achieve there could be multiple ways, to use right weights & parameters are the most effective part of it.Thanks for sharing this valuable information.

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Explaining the fundamentals of the P-value;

05 August 2020 | Abhishek Mishra

Many times, I have seen data science professionals who know very well what is p-values but they struggle to explain it. I have also seen many professionals who don’t want to get into technical details but want to know more and understand why it is so important.

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GULP: A DEVOPS Based Tool for Web Applications;

24 July 2020 | Balakrishnan Subramanian

This article is very informative and the steps which are been soon can be easily approcable .A lit more effective and efficient way the author tries to summarise the step here.

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Ensemble Machine Learning Explained in Simple Terms;

19 July 2020 | Fatai Anifowose

That's a good article and very well explained.I was using EML without realizing it... in form of Random Forest Algorithm.

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Membership Drive;

16 July 2020 | Mohammed Khursheed Akhtar

It is really very excellent and eye-catching website. Thanks Nr. Chris for your kind gestures and support to grant me full membership status. I will try my level best to do some extraordinary things for Data Science. Inshaa Allah (God Willing).

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INNOVATING THE LEARNING EXPERIENCE THROUGH EDUCATIONAL TECHNOLOGY: A DIGITAL INSIGHT;

03 July 2020 | Balakrishnan Subramanian

The Next Generation Digital Learning Environment (NGDLE) is considered as a ecosystem - a learning situation comprising of learning apparatuses and segments that stick to normal guidelines. While the customary Learning Management System (LMS) gives regulatory capacities, the NGDLE is planned to straightforwardly bolster learning.

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Data Science and Econometrics;

29 June 2020 | Olawale Akintunde

What is the correlation between Data Science and Econometrics.I have been thinking to find out if Data Science can stand alone without Econometrics. Will it rather be wise to say Econometrics forms a better modelling blocks on which Data Science thrive. I will like to know the correlation between this two fields. Thanks

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Knowing all about Outliers in Machine Learning;

23 June 2020 | Mayank Tripathi

One more thing which i missed in the article, that presence of outliers affects the distribution of the data. Let's examine what can happen to a data set with outliers. For the sample data set: 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4 We find the following: mean, median, mode, and standard deviation Mean = 2.58 Median = 2.5 Mode = 2 Standard Deviation = 1.08 If we add an outlier to the data set: 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4, 400 The new values of our statistics are: Mean = 35.38 Median = 2.5 Mode = 2 Standard Deviation = 114.74 It can be seen that having outliers often has a significant effect on the mean and standard deviation and hence affecting the distribution. We must take steps to remove outliers from our data sets. One of the easiest way to handle this is log transformation.Hope this information will help you.

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LATEST NEWS

TOP 10 DATA SCIENCE TRENDS FOR THIS DECADE

11 April 2021

The presence of data in every field that you can think of is what turns out to be a reason why organizations are showing interest in data science.

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Sony patents AI that adjusts gameplay difficulty when you’re struggling

07 February 2021

If battles with video game bosses make you throw your controller at the wall, Sony is working on a new AI feature that could make your future foes more beatable.

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Top 7 Big Data Trends to Dominate 2021

04 February 2021

With the rapid growth of big data, emerging trends like cloud computing, actionable data, hyperautomation, and cloud automation will be the deciding factors to reshape how businesses function in 2021.

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AI in the EU: Balancing benefit and control

02 January 2021

The definition of AI should come down to its application, with risk assessments focusing on the intended use of the application and the type of impact resulting from the AI function.

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ARTIFICIAL INTELLIGENCE IN 2021: ENDLESS OPPORTUNITIES AND GROWTH

02 January 2021

Moving into 2021, Artificial Intelligence will keep on going about as a principle technological pioneer for years to come.

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Teesside energy firm seals deal with global tech AI company

22 December 2020

A Teesside energy firm has completed a deal with a global tech firm which could help process industry firms cut costs by millions.

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AI will take away lots of jobs. And we are nowhere near ready to replace them

22 December 2020

The scale of the challenge that automation poses to the jobs market needs to be met with much stronger action to up-skill the workforce, finds a new report published by a committee in the UK Parliament.

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Japan to fund AI matchmaking to boost birth rate

16 December 2020

From next year it will subsidise local governments already running or starting projects that use AI to pair people up. Last year the number of babies born in Japan fell below 865,000 - a record low. The fast-greying nation has long been searching for ways to reverse one of the world's lowest fertility rates. Boosting the use of AI tech is one of its latest efforts.

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AI can predict Twitter users likely to spread disinformation before they do it

16 December 2020

A new artificial intelligence-based algorithm that can accurately predict which Twitter users will spread disinformation before they actually do it has been developed by researchers from the University of Sheffield.

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Machine Learning 101: Part 1

25 November 2020

The purpose of this series of articles is to provide a complete guide (from data to predictions) to machine learning, for .NET developers in a .NET ecosystem, and that is possible now using Microsoft ML.NET and Jupyter Notebooks. Even more, you don’t have to be a data scientist to do machine learning.

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AI Machine Learning Innovation to Develop Chemical Library for Drug Discovery

25 November 2020

Purdue University innovators have introduced chemical reactivity flowcharts to help chemists interpret reaction outcomes using statistically robust machine learning models trained on a small number of reactions. The work is published in Organic Letters.

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Fujitsu labs takes machine learning record

25 November 2020

Fujitsu Labs has achieved the highest performance on the MLPerf HPC benchmark, which measures large-scale machine learning processing on supercomputers.

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TOP 6 MACHINE LEARNING TRENDS OF 2021

25 November 2020

With the surge in demand and interest in these technologies, various new patterns are ascending during this space. Simply if you’re a tech capable or related to innovation in some capacity, it’s exciting to see what’s next inside the space of machine learning.

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Exploring The Power Of Data In Quantum Machine Learning

25 November 2020

Quantum computers have the capability to develop quantum machine learning algorithms. These algorithms can achieve better performance for modeling quantum-mechanical systems such as molecules, catalysts, or high-temperature superconductors. Since it is difficult for classical computers to handle the interference of the exponentially evolving states in the quantum world, quantum computers are expected to have an advantage in quantum originated-machine learning problems. The quantum advantage extends to machine learning problems in the classical domain, for example, computer vision or natural language processing.

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Machine learning: A breakthrough in the study of stellar nurseries

25 November 2020

Artificial intelligence can make it possible to see astrophysical phenomena that were previously beyond reach. Astronomers present the most comprehensive observations yet carried out of one of the star-forming regions closest to the Earth.

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INFORMATION ON DATA SCIENCE

The Data Science Foundation is committed to improving decision making. We believe that the use of data can improve decision making, but only if the social and environmental impact of decisions are evaluated alongside the knowledge and insight created though analytics. We work hard to help our members improve their decision making. To make good decisions today and to make better decisions tomorrow.

BIG DATA

We help organisations new to evidence-based decision making; collect, process and analyse data. We help them appreciate the meaning hidden in their data so that they can understand more about the landscape in which they operate. We then help organisations who already have the expertise to collect data and create insight, to consider the moral implications of their actions. To think about the social and environmental impact of what the data might suggest is the best possible course of action.