Time for some Data World round-up.
- State of Data Science 2021
- Promoting trust in data by World Bank
- IBM: Difference between Structured and Unstructured data
- 50 Global Hubs for Top AI Talent & more updates
Keep reading to stay up to date!
- State of Data Science 2021: Anaconda
The 2021 State of Data Science report by Anaconda provides insight into the trends and changes in the data science industry along with areas of growth, the impact of COVID-19, and more. This report features more than 4,200 responses from individuals using data science and machine learning tools in more than 140 countries.
"How did COVID-19 influence your organization's investment in Data Science?"
- World Bank: Promoting trust in data through multistakeholder data governance
Data has an incredible potential for development but at the same time can be misused in a hurtful fashion due to weak data governance or data management. "Enabling trust, value, and equity in data use requires adopting an approach to data governance that is informed by all people."
- Finding the difference between Structured and Unstructured data with IBM
Debriefing the difference between Structured and Unstructured data, their pros and cons, data tools, and their use cases.
- 3 Best Data Practices to take your skills to next level
Tableau’s Senior Curriculum Strategy Manager Sue Kraemer explains the 3 best data visualization tips and data practices to present the best visualization for Iron Viz: Student Edition. Tableau is accepting entries till December 31st.
- How Marks & Spencer is using Data Science education to upskill their internal talent?
Marks & Spencer is unlocking the power of Data Science that includes Master’s degree apprenticeships as well as promoting Data Literacy. “I don’t think anyone would have expected that M&S would be the first retailer to launch a data science and AI apprenticeship program. And yet here we are.”
- Harvard Business Review:50 Global Hubs for Top AI Talent
"As AI expands into more and more facets of our lives, there is also more scrutiny on who is developing it. Building ethical AI that works for everyone will require a diverse workforce that brings a broad range of perspectives. To aid in that effort, the authors have compiled the top 50 cities for AI talent and analyzed how diverse the population of developers is in each. This can help companies direct their recruiting and hiring as they try to build a broader, more diverse AI workforce."
- AWS's initiative to help underserved students prep for careers in AI and ML
The AWS & ML Scholarship program is an attempt to bring diversity into the field of AI/ML. This program is aimed at the underserved and underrepresented students in tech, which include women, people with disabilities, and members of the LGBTQ+ community. This program starts on March 1, 2022, and each year 2,000 students receive this scholarship.
- By @docmilanfar
“Abstract:— Peyman 𝕄𝕀𝕃𝔸ℕ𝔽𝔸ℝ (@docmilanfar) October 24, 2021
We propose a generative model for super-resolution” pic.twitter.com/jy0YSXANA3
- By @fchollet
In a world so focused on beating task-specific benchmarks, on training ever larger deep learning models on ever larger datasets, trying instead to ask the right questions is an act of rebellion.— François Chollet (@fchollet) December 13, 2021
- By @mitsmr
"Synthetic data’s most obvious benefit is that it eliminates the risk of exposing critical data and compromising the privacy and security of companies and customers." —@fernandolucini https://t.co/RrjMbPii0G— MIT Sloan Management Review (@mitsmr) October 22, 2021
Curious to know more in the data world? This newsletter keeps you updated by providing brief bits of articles, top news, and trending tweets. Posted every Monday and Friday, this Data Newsletter is a way to stay informed in the field of data.
Stay tuned for the next edition!