2020 Oct Opinions
All (69) | Events (1) | News, Education (8) | Opinions (13) | Top Stories, Tweets (7) | Tutorials, Overviews (40)
- Ain’t No Such a Thing as a Citizen Data Scientist
- Oct 26, 2020.
With learn-it-quick courses on data science popping up nearly a dime a dozen, more people are obtaining the sense they can dive into professional work with minimal qualifications and scant experience or practice. While the notion of a 'Citizen Scientist' is intended to simply support a broader appreciation of science and the scientific process to more people, the 'Citizen Data Scientist' is being inappropriately seen as a fast track to a new career.
- Software 2.0 takes shape
- Oct 23, 2020.
Software developers remain in very high demand as many organizations continue to experience workloads that far exceed available talent. AI-enhanced approaches that automate more areas of the software development lifecycle are in development with interesting potentials for how machine learning and natural language processing can significantly impact how software is designed, developed, tested, and deployed in the future.
- The unspoken difference between junior and senior data scientists
- Oct 22, 2020.
The unspoken difference between junior and senior data scientists? It’s not what you think.
- The Ethics of AI
- Oct 21, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about a very important subject - the ethics of AI.
- 5 Must-Read Data Science Papers (and How to Use Them)
- Oct 20, 2020.
Keeping ahead of the latest developments in a field is key to advancing your skills and your career. Five foundational ideas from recent data science papers are highlighted here with tips on how to leverage these advancements in your work, and keep you on top of the machine learning game.
- Cartoon: Cloud Dating
- Oct 17, 2020.
New KDnuggets cartoon looks at how AI can transform love and romance.
- Algorithms of Social Manipulation
- Oct 9, 2020.
As we all continuously interact with each other and our favorite businesses through apps and websites, the level at which we are being tracked and monitored is significant. While the technologies behind these capabilities provide us value, the tech companies can also influence our decisions on where to click, spend our money, and much more.
- 6 Lessons Learned in 6 Months as a Data Scientist
- Oct 8, 2020.
When transitioning into a Data Science career, a new mindset toward collaboration, data, and reporting is required. Learn from these recommendations on approaches you should consider to successfully develop into your dream job.
- 5 Challenges to Scaling Machine Learning Models
- Oct 7, 2020.
ML models are hard to be translated into active business gains. In order to understand the common pitfalls in productionizing ML models, let’s dive into the top 5 challenges that organizations face.
- Here are the Most Popular Python IDEs/Editors
- Oct 6, 2020.
Jupyter Notebook continues to lead as the most popular Python IDE, but its share has declined since the last poll. The top 4 contenders have remained the same, but only one has significantly improved its share. We also examine the breakdown by employment and region.
- 5 Concepts Every Data Scientist Should Know
- Oct 2, 2020.
Once a Data Scientist, there are certain skills you will apply each and every day of your career. Some of these might be common techniques you learned during your education, while others may develop fully only after you become more established in your organization. Continuing to hone these skills will provide you with valuable professional benefits.
- Comparing the Top Business Intelligence Tools: Power BI vs Tableau vs Qlik vs Domo
- Oct 2, 2020.
How smart are your organizations’ decisions? Do you have the right information to make those decisions in the first place?
- Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science
- Oct 1, 2020.
Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.