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Data Science


Web Scraping using Selenium

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Web Scraping is a popular methodology to extract data from websites. This is often done to derive insights for Sentiment Analysis, Predicting User preferences, Cross-Selling products, etc. Some of the real-life examples of web scraping include – extracting data for pricing analysis, user ratings for movie sentiment analysis, corporate admin tasks to read and classify log files in an HTML, search bots trying to make sense of a results page. While web scraping activity does not provide intelligence of its own, as we have seen above the data extracted can be useful in multiple ways. A more common use case would be a start-up eCommerce website trying to set a price on its products based on market research on competitors.


IBM Research releases differential privacy library that works with machine learning

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Differential privacy has become an integral way for data scientists to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual's data to be distinguished or re-identified. To help more researchers with their work, IBM released the open-source Differential Privacy Library. The library "boasts a suite of tools for machine learning and data analytics tasks, all with built-in privacy guarantees," according to Naoise Holohan, a research staff member on IBM Research Europe's privacy and security team. "Our library is unique to others in giving scientists and developers access to lightweight, user-friendly tools for data analytics and machine learning in a familiar environment–in fact, most tasks can be run with only a single line of code," Holohan wrote in a blog post on Friday. "What also sets our library apart is our machine learning functionality enables organizations to publish and share their data with rigorous guarantees on user privacy like never before."


Data Scientist - IoT BigData Jobs

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DuPont has a rich history of scientific discovery that has enabled countless innovations and today, we're looking for more people, in more places, to collaborate with us to make life the best that it can be. DuPont Pioneer is aggressively building Big Data and Predictive Analytics capabilities in order to deliver improved services to our customers. We seek a strong data scientist with a background in math, statistics, machine learning and scientific computing to join our team. This is a critical position with the potential to make immediate, significant impact on our business. The successful candidate will have an extensive background in statistical computing and machine learning through courses or thesis/dissertation, and proven experience validating models against experimental data.


How Does AIOps Integrate AI and Machine Learning into IT Operations?

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This calls for an increase in budgetary allocation increase and more computing power (that can be leveraged) to be added from outside core IT. AIOps bridges the gap between service management, performance management, and automation within the IT eco-system to accomplish the continuous goal of IT operation improvements. AIOps creates a game plan that delivers within the new accelerated IT environments, to identify patterns in monitoring, service desk, capacity addition and data automation across hybrid on-premises and multi-cloud environments.


Businesses want to use Big Data without compromising privacy

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Use of this site constitutes acceptance of our Terms of Use and Privacy Policy Do Not Sell My Info Ad Choices FORTUNE is a trademark of Fortune Media IP Limited, registered in the U.S. and other countries. FORTUNE may receive compensation for some links to products and services on this website. Offers may be subject to change without notice. Quotes delayed at least 15 minutes. Market data provided by Interactive Data.


Visualizing Principal Components for Images - Hi! I am Nagdev

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Principal Component Analysis (PCA) is a great tool for a data analysis projects for a lot of reasons. If you have never heard of PCA, in simple words it does a linear transformation of your features using covariance or correlation. I will add a few links below if you want to know more about it. Some of the applications of PCA are dimensional reduction, feature analysis, data compression, anomaly detection, clustering and many more. The first time I learnt about PCA, it was not easy to understand and quite confusing.


Zicklin Grad Students Take Top Spot in Pitney Bowes Data Challenge - Zicklin School of Business

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Nearly five dozen students from Baruch College and the Zicklin School of Business got to show off their data-crunching skills recently when they participated in the Baruch College – Pitney Bowes Data Challenge, held on May 1. The winning team of Zicklin graduate students -- Drace (Yilei) Zhan (MS Statistics, '20), Nishtha Ram (MS Quantitative Methods & Modeling, '21), Huimin Chen (MS Information Systems, '21), Kang Li (MS QMM, '20), and Rosario Campoverde (MBA, '20) -- outperformed 50 other undergraduate and graduate students across Baruch and Zicklin to take first place. The competition was the culmination of a year-long collaboration among Pitney Bowes and the Paul H. Chook Department of Information Systems and Statistics, the Graduate Career Management Center, and the Starr Career Development Center. The partnership included seminars held throughout the year on machine learning, design thinking, marketing analytics, and other topics, presented by Pitney Bowes data scientists; and a free bootcamp on Python and AWS that was led by Zicklin professors. It was funded by a $10,000 grant from the NYC/CUNY Workforce Development Initiative.


Linear Programming for Data Science and Business Analysis

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In this course you will learn all about the mathematical optimization of linear programming for data science and business analytics. This course is very unique and have its own importance in their respective disciplines. The data science and business study heavily rely on optimization. Optimization is the study of analysis and interpreting mathematical data under the special rules and formula. The length of the course is more than 6 hours and there are total more than 4 sections in this course.


Global Big Data Conference

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Since its advent, machine learning has altered the world of technology one industry vertical at a time. Starting from the predictive analytics engines that generate recommendations to the artificial intelligence technology used in a myriad of antivirus applications, this is all machine learning at play. But what happens when these systems get confused or, worse, get attacked and purposefully manipulated into making wrong decisions? Thus, like any other technology, it is crucial to analyze machine learning's advancing canvas and the potential risks of misuse that comes with it. First, let's answer the question, "What is machine learning?"


How Does AIOps Integrate AI and Machine Learning into IT Operations?

#artificialintelligence

This calls for an increase in budgetary allocation increase and more computing power (that can be leveraged) to be added from outside core IT. AIOps bridges the gap between service management, performance management, and automation within the IT eco-system to accomplish the continuous goal of IT operation improvements. AIOps creates a game plan that delivers within the new accelerated IT environments, to identify patterns in monitoring, service desk, capacity addition and data automation across hybrid on-premises and multi-cloud environments.