Étiquette : analysis
Pros & Cons Of Choosing A Career In Data Science
The internet may be saturated with articles on why data science is the ‘sexiest job of the 21st century’, but little has been spoken about its possible cons. The draw of a career in this field is undeniable — it is in demand, pays well, and has a right mix…
Eight Questions Data Scientists Should Ask Recruiters During Job Interviews
Data science aspirants should be mindful of the fact that recruiters are always looking for strong communicators. Source : https://analyticsindiamag.com/what-data-science-aspirants-should-ask-recruiters-during-job-interviews/?utm_source=rss&utm_medium=rss&utm_campaign=what-data-science-aspirants-should-ask-recruiters-during-job-interviews Date : March 2, 2020 at 01:41PM Tag(s) : #AI ENG Share this… Email Facebook Twitter Linkedin Whatsapp Print
6 In Demand Cybersecurity Job Roles For 2020
As more data breaches take place, the requirements and salary for cybersecurity professionals are increasing. With ransomware, hacks and threats becoming more common, an organisation’s need to concentrate more on their cybersecurity teams has increased. There are already many popular job roles when it comes to cybersecurity like application security…
Making Sense of the Hype Cycle for Artificial Intelligence
Summary: If you’re planning your AI/ML business strategy watch out for the confusion in categories and overly risky ratings given by some research and review sources. Read the research, then consult with your own data scientists for a better evaluation of risk. It’s likely not as bad as you think….
Most Commonly Asked Interview Questions On Data Visualisation
For organisations, the amount of influx in data has to be represented and communicated in a manner which is well understood and has relevant information. Most of the data present in the text format might not reveal the patterns and trends that are needed to make use of the data,…
AI in the Fight to Detect and Cure Coronavirus
The COVID-19 coronavirus is rapidly spreading around the globe, threatening communities, alarming financial markets and, in many cases, forcing national epidemic response teams to quickly update and implement years-old plans. As those researchers race to apply today’s technology to detecting and combating the virus, many are talking about how –…
History of smart cities: Timeline
The journey to smart cities goes way back to the 1970s, when Los Angeles created the first urban big data project: “A Cluster Analysis of Los Angeles”. Source : https://www.verdict.co.uk/smart-cities-timeline/ Date : February 29, 2020 at 12:22AM Tag(s) : #SMARTCITY ENG Share this… Email Facebook Twitter Linkedin Whatsapp Print
#Privacy: Data analytics trends in 2020
One of the key technology highlights of the past decade has been the exponential growth in organisational data. Whether by accident or design, the amount of data available to every business truly exploded. Source : https://gdpr.report/news/2020/02/28/privacy-data-analytics-trends-in-2020/ Date : February 28, 2020 at 12:54PM Tag(s) : #RGPD ENG Share this… Email…
The Many Faces of AI in Clinical Trials
AI is being applied in several aspects for the clinical trial process today. From analyzing real-world data and scientific information to providing improved patient stratification and predictive outcomes, and assisting with different aspects of clinical trial operations. Here are some of the technologies using AI and machine learning in the…
How AI in Healthcare Is Changing the Industry
AI in healthcare is something that is revolutionizing the industry and medical treatment that we as the patients receive. But AI, in general, is making inroads into virtually every field and aspect of society. Healthcare AI companies like NVIDIA healthcare and Google DeepMind Health are breaking new ground, with innovations…
London-based Gyana raises $3.9M for a no-code approach to data science
Coding and other computer science expertise remain some of the more important skills that a person can have in the working world today, but in the last few years, we have also seen a big rise in a new generation of tools providing an alternative way of reaping the fruits…
An Introductory Guide To AI & Machine Learning
Artificial intelligence (AI) is a field of study, where researchers try to enhance the ability of systems to learn automatically without human intervention. To achieve this, researchers and developers use historical data and train Machine Learning (ML) models with different techniques. Source : https://analyticsindiamag.com/an-introductory-guide-to-ai-machine-learning/?utm_source=rss&utm_medium=rss&utm_campaign=an-introductory-guide-to-ai-machine-learning Date : February 27, 2020 at…
How AI is Automating and Improving Software Development
Software is eating the world, but now, AI is eating software development, augmenting the work of chronically understaffed programming teams, allowing developers to focus more on higher-level tasks and less on scut work. And it’s only in its infancy. Source : https://www.enterpriseai.news/2020/02/25/how-ai-is-automating-and-improving-software-programming/?utm_source=rss&utm_medium=rss&utm_campaign=how-ai-is-automating-and-improving-software-programming Date : February 25, 2020 at 10:13PM Tag(s)…
‘Shadow IoT’ Undermining Network Security
The majority of Internet of Things transactions are unsecured, adding a new enterprise security threat as industrial and retail IoT traffic begins to ramp up. Source : https://www.enterpriseai.news/2020/02/25/shadow-iot-undermining-network-security/?utm_source=rss&utm_medium=rss&utm_campaign=shadow-iot-undermining-network-security Date : February 25, 2020 at 08:12PM Tag(s) : #AI ENG Share this… Email Facebook Twitter Linkedin Whatsapp Print
How To Start A Career In Data Science
A data scientist is someone who helps an organisation to make critical decisions through data analysis, modelling, visualisation, among others. According to the survey reports, Data Science and analytics ecosystem has been witnessing an overall growth in the number of jobs with India contributing to 6% of open job openings…
#Privacy: Despite cybersecurity confidence, organisations discover data stored in unprotected locations
Cybersecurity vendor Netwrix, has released its 2020 Data Risk & Security Report which studies how organizations treat sensitive and regulated data during each stage of its lifecycle. Source : https://gdpr.report/news/2020/02/26/privacy-despite-cybersecurity-confidence-organisations-discover-data-stored-in-unprotected-locations/ Date : February 26, 2020 at 08:46AM Tag(s) : #RGPD ENG Share this… Email Facebook Twitter Linkedin Whatsapp Print
The Ultimate Guide To Getting Started With Cybersecurity
Cybersecurity has been one of the hottest professions ever since the Y2K crisis. From cyber-attacks to security vulnerabilities, ever since the dawn of the millennium, organisations across the globe have been consistently targeted. This scenario has given way to a huge opportunity for professionals willing to enter the security domain….
Smart Parking Solutions Market Volume Analysis, size, share and Key Trends 2018 – 2026
Smart city projects offer sustainability in addition to enhanced performance. With the transformation of a city into a smart city, authorities around the … Source : https://www.instanttechnews.com/technology-news/2020/02/23/smart-parking-solutions-market-volume-analysis-size-share-and-key-trends-2018-2026/ Date : February 23, 2020 at 08:38PM Tag(s) : #SMARTCITY ENG Share this… Email Facebook Twitter Linkedin Whatsapp Print
The difference between Statistics and Data Science: Big Data and Inferential Statistics
Based on these, I address the question of ‘The difference between Statistics and Data Science’. Traditionally, most people, including me, would say that ‘statistics came first and Data Science builds upon statistics’. Source : http://www.datasciencecentral.com/xn/detail/6448529:BlogPost:933743 Date : February 24, 2020 at 02:16AM Tag(s) : #DATA ENG Share this… Email Facebook…
10 Datasets For Data Cleaning Practice For Beginners
In order to create quality data analytics solutions, it is very crucial to wrangle the data. The process includes identifying and removing inaccurate and irrelevant data, dealing with the missing data, removing the duplicate data, etc. Thus, eliminating the major inconsistencies and making the data more efficient to work with….