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Deep Autoregressive Models
/in Artificial Intelligence, Data Mining, Data Science, Deep Learning, Machine Learning, Main Category/by Sunil YadavIn this blog article, we will discuss about deep autoregressive generative models (AGM). Autoregressive models were originated from economics and social science literature on time-series data where obser- vations from the previous steps are used to predict the value at the current and at future time steps
How to ensure occupational safety using Deep Learning – Infographic
/in Artificial Intelligence, Data Science, Deep Learning, Insights, Machine Learning, Main Category, Use Cases/by Benjamin AunkoferHow to ensure occupational safety through automatic risk detection using Deep Learning – Infographic
Four essential ideas for making reinforcement learning and dynamic programming more effective
/in Artificial Intelligence, Data Science, Deep Learning, Machine Learning, Predictive Analytics/by Yasuto TamuraThis is the third article of the series My elaborate study notes on reinforcement learning. 1, Some excuses for writing another article on the same topic In the last article […]
How Deep Learning drives businesses forward through automation – Infographic
/in Artificial Intelligence, Deep Learning, Machine Learning, Main Category, Use Cases/by Benjamin AunkoferIn cooperation between DATANOMIQ, my consulting company for data science, business intelligence and process mining, and Pixolution, a specialist for computer vision with deep learning, we have created an infographic about a very special use case for companies with deep learning: How to protect the corporate identity of any company by ensuring consistent branding with automated font recognition.
What is Portfolio Risk Management in Python?
/in Python/by Shannon FlynnData science is a crucial industry, with multiple processes today relying on it. One of its more helpful and intriguing applications is in investing, where it helps investors make more informed decisions. Practices like portfolio management in Python help take the guesswork out of this notoriously risky undertaking.
How To Perform High-Quality Data Science Job Assessments in 4 Steps
/in Carrier, Gerneral, Jobs/by Arianna LupiIn 2009, Google Chief Economist Hal Varian said to the McKinsey Quarterly that “the sexy job in the next 10 years will be statisticians.” At the time, it was hard […]
How To Perform High-Quality Data Science Job Assessments in 4 Steps
/in Carrier, Gerneral, Insights/by Arianna LupiSo, you’ll want to choose your data scientists carefully, but how do you do that? Resumes and portfolios might seem impressive, but how do you actually find out if someone has the skills you’re looking for—especially if you don’t have anyone on board yet that knows what to ask.
10 Best Resources To Learn Data Science Online in 2022
/in Carrier, Certification / Training, Education / Certification, Gerneral/by Akash TripathiIncreasing technology and big data mean that organizations must leverage their data in order to deliver more powerful products and services to the world by analyzing that data and gaining insight, which is what the term “Data Science” means. You can jumpstart your career in Data Science by utilizing any of the resources listed above. Make sure you have the right resources and certifications. Now is the time to work in the data industry.
Mainframe Modernization: Making It Happen
/in Insights, Main Category/by Edward HuskinMainframe modernization is a major undertaking that presents a host of options for every organization. These options will vary depending on a number of factors, including business size, tenure, and industry. The following, however, are a few of the key considerations in modernization.
5 Best Practices for Performing Data Backup and Recovery
/in Datacenter, Main Category/by Shannon FlynnData backup and recovery are critical for any organization in the digital age. The field of data science has developed advanced, secure, user-friendly backup and recovery technology over recent years. For anyone new to data backup and recovery, it can be challenging knowing where to start, especially when dealing with large quantities of data. There are some best practices in data backup and recovery that are beneficial for any user or organization. These tips will provide a jumping-off point for creating a customized data protection strategy.