Opinions, Interviews, Reports
We welcome guest blogs and opinions - see submission guidelines.
Latest:
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How I Got Better at Machine Learning - Nov 13, 2019.
Check out this author's collection of tips and tricks that I learned over the years to get better at Machine Learning. -
How to Speed up Pandas by 4x with one line of code - Nov 12, 2019.
While Pandas is the library for data processing in Python, it isn't really built for speed. Learn more about the new library, Modin, developed to distribute Pandas' computation to speedup your data prep. -
How Data Analytics Can Assist in Fraud Detection - Nov 11, 2019.
A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies. -
What is Data Science? - Nov 8, 2019.
Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist. -
The Last Defense Against Another AI Winter - Nov 6, 2019.
My short answer is this: Yes, another AI Winter will be here if you don’t deploy more ML solutions. You and your Data Science teams are the last line of defense against the AI Winter. You need to solve five key challenges to keep the momentum up. -
How to Become a Successful Healthcare Data Analyst - Nov 5, 2019.
Are you interested in starting your career in the data analysis domain? Read this informative blog on how to get your career off the ground.
October:
- How to Make an Agile Team Work for Big Data Analytics
- How Data Labeling Facilitates AI Models
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Why is Machine Learning Deployment Hard?
Developing an excellent machine learning model is one thing. Deploying it to production is another. Consider these lessons learned and recommendations for approaching this important challenge to help ensure value from your AI work. - About Google’s Self-Proclaimed Quantum Supremacy and its Impact on Artificial Intelligence
- Seven Myths About the True Costs of AI Systems
- Addressing the Growing Need for Skills in Data Science
- Bye Data Scientists, Hello AI? Not Likely!
- 5 Tips for Novice Freelance Data Scientists
- Artificial Intelligence: Salaries Heading Skyward
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How to Become a (Good) Data Scientist – Beginner Guide
A guide covering the things you should learn to become a data scientist, including the basics of business intelligence, statistics, programming, and machine learning. - Using DC/OS to Accelerate Data Science in the Enterprise
- Top 7 Things I Learned in my Data Science Masters
- Choosing a Machine Learning Model
- There is No Such Thing as a Free Lunch
- The problem with metrics is a big problem for AI
- 8 Paths to Getting a Machine Learning Job Interview
- Lemma, Lemma, Red Pyjama: Or, doing words with AI
- Four questions to help accurately scope analytics engineering project
- Data Science is Boring (Part 2)
- Why the ‘why way’ is the right way to restoring trust in AI
- Overcoming Deep Learning Stumbling Blocks
- Training a Machine Learning Engineer
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A European Approach to Master’s Degrees in Data Science
Data science education in Europe has been reevaluated and new recommendations are leading the way to the next generation of data science Master's courses to better support and train students.
