2020 Jun Opinions
All (83) | Events (2) | News, Education (7) | Opinions (19) | Top Stories, Tweets (10) | Tutorials, Overviews (45)
- Stop training more models, start deploying them - Jun 30, 2020.
We are hardly living up to the promises of AI in healthcare. It’s not because of our training, it’s because of our deployment.
- The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP) - Jun 29, 2020.
Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.
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How Much Math do you need in Data Science? - Jun 26, 2020.
There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation. - Exploring the Real World of Data Science - Jun 26, 2020.
An article highlighting things I’ve learned in the real world about data science.
- Data Science Tools Popularity, animated - Jun 25, 2020.
Watch the evolution of the top 10 most popular data science tools based on KDnuggets software polls from 2000 to 2019.
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Learning by Forgetting: Deep Neural Networks and the Jennifer Aniston Neuron - Jun 25, 2020.
DeepMind’s research shows how to understand the role of individual neurons in a neural network. - Machine Learning Engineer vs Data Scientist (Is Data Science Over?) - Jun 25, 2020.
What has been happening to the definition of Data Scientist over the past 5 years? Does it still exist or has it morphed into a new version of its old self? Learn more about the recent trends in job descriptions and salaries for data scientists, ML engineers, and others to best understand the best fit for your career trajectory and interests.
- Tools to Spot Deepfakes and AI-Generated Text - Jun 23, 2020.
The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.
- Top 6 Reasons Data Scientists Should Know Java - Jun 12, 2020.
There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.
- Upgrading the Brand Mobile App with Machine Learning - Jun 11, 2020.
The tech progress in mobile app development, as well as digital enhancements, have created new chances for brands to allure and retain customers. In bridging the individualization gap, Machine Learning comes to the rescue.
- How to make AI/Machine Learning models resilient during COVID-19 crisis - Jun 11, 2020.
COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. Data Science teams must invest effort in post-model tracking and management as well as deploy an agility in the AI/ML process to curb problems related to concept shift.
- Fighting Disease with Data: Q&A with Epidemiologist Amrish Baidjoe - Jun 11, 2020.
Data science tools are powerful for investigating the current pandemic and other outbreaks, when accurate and actionable data are crucial. Epidemiologist and R Epidemics Consortium leader Amrish Baidjoe shared his insights into using data science to fight disease, from modeling to automation to new technologies.
- New Poll: What was the largest dataset you analyzed / data mined? - Jun 9, 2020.
Take part in KDnuggets latest survey to have your voice heard, and let the community know what the largest dataset size you have worked with is.
- GPT-3, a giant step for Deep Learning and NLP? - Jun 9, 2020.
Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.
- Nitpicking Machine Learning Technical Debt - Jun 8, 2020.
Technical Debt in software development is pervasive. With machine learning engineering maturing, this classic trouble is unsurprisingly rearing its ugly head. These 25 best practices, first described in 2015 and promptly overshadowed by shiny new ML techniques, are updated for 2020 and ready for you to follow -- and lead the way to better ML code and processes in your organization.
- Why Do AI Systems Need Human Intervention to Work Well? - Jun 5, 2020.
All is not well with artificial intelligence-based systems during the coronavirus pandemic. No, the virus does not impact AI – however, it does impact humans, without whom AI and ML systems cannot function properly. Surprised?
- If you had to start statistics all over again, where would you start? - Jun 5, 2020.
If you are just diving into learning statistics, then where do you begin? Find insight from those who have tread in these waters before, and see what they might have done differently along their personal journeys in statistics.
- 3 Key Data Science Questions to Ask Your Big Data - Jun 3, 2020.
The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.
- Don’t Democratize Data Science - Jun 2, 2020.
A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist make.
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