2020 Jul Opinions
All (87) | Events (3) | News, Education (7) | Opinions (16) | Top Stories, Tweets (9) | Tutorials, Overviews (52)
- Is depth useful for self-attention? - Jul 27, 2020.
Learn about recent research that is the first to explain a surprising phenomenon where in BERT/Transformer-like architectures, deepening the network does not seem to be better than widening (or, increasing the representation dimension). This empirical observation is in contrast to a fundamental premise in deep learning.
- Recommender Systems in a Nutshell - Jul 23, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about recommender systems and the ways they are used.
- Monitoring Apache Spark – We’re building a better Spark UI - Jul 23, 2020.
Data Mechanics is developing a free monitoring UI tool for Apache Spark to replace the Spark UI with a better UX, new metrics, and automated performance recommendations. Preview these high-level feedback features, and consider trying it out to support its first release.
- Why would you put Scikit-learn in the browser? - Jul 22, 2020.
Honestly? I don’t know. But I do think WebAssembly is a good target for ML/AI deployment (in the browser and beyond).
- 10 Steps for Tackling Data Privacy and Security Laws in 2020 - Jul 22, 2020.
Data privacy laws, such as the CCPA, GDPR, and HIPAA, are here to stay and significantly impact everyone in the digital era. These steps will guide organizations to prepare for compliance and ensure they support the fundamental privacy rights of their customers and users.
- What I learned from looking at 200 machine learning tools - Jul 21, 2020.
While hundreds of machine learning tools are available today, the ML software landscape may still be underdeveloped with more room to mature. This review considers the state of ML tools, existing challenges, and which frameworks are addressing the future of machine learning software.
- Data Science MOOCs are too Superficial - Jul 20, 2020.
Most massive open online courses are too superficial because they offer introductory-level courses. For in-depth knowledge, more is needed to increase your knowledge and expertise after establishing a foundation.
- The Bitter Lesson of Machine Learning - Jul 15, 2020.
Since that renowned conference at Dartmouth College in 1956, AI research has experienced many crests and troughs of progress through the years. From the many lessons learned during this time, some have needed to be re-learned -- repeatedly -- and the most important of which has also been the most difficult to accept by many researchers.
- Deep Learning in Finance: Is This The Future of the Financial Industry? - Jul 10, 2020.
Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.
- What every Data Scientist needs to learn from Business Leaders - Jul 10, 2020.
You've learned so much to become a Data Scientist. Now, it's time to kick it up to the next level with advanced soft skills -- because these are important to the business for which you empower to make better decisions. Learning from the business leaders you support will help you develop a broader set of enhanced skills that will boost your Data Science quality and output.
- Why Learn Python? Here Are 8 Data-Driven Reasons - Jul 10, 2020.
Through this blog, I will list out the major reasons why you should learn Python and the 8 major data-driven reasons for learning it.
- 5 Innovative AI Software Companies You Should Know - Jul 8, 2020.
While machine learning is impacting organizations around the world, some are driving forward the real-world applications of innovative AI. Check out these interesting companies to watch for exciting new progress this year.
- Scope and Impact of AI in Agriculture - Jul 6, 2020.
The major advantage of focusing on AI-based methods is that they tackle each of the challenges faced by farmers from seed sowing to harvesting of crops separately and rather than generalising, provide customised solutions to a specific problem.
- Data Scientists Have Developed a Faster Way to Reduce Pollution, Cut Greenhouse Gas Emissions - Jul 3, 2020.
Data science is helping with one of the world's most pressing issues. Read about an approach and specific steps being taken by data scientists to quickly reduce pollution and greenhouse gas emissions.
- Largest Dataset Analyzed – Poll Results and Trends - Jul 1, 2020.
The results show that despite the deluge of Big Data, large majority still works in Gigabyte or Megabyte-size datasets. Data Scientists work with the largest-size datasets, followed by Data Engineers, Data Analysts, and Business Analysts. Read more for details.
- How to Build Your Data Science Competency for Post-COVID Future - Jul 1, 2020.
Data science is helping healthcare organizations and businesses navigate the current crisis more effectively. Find out how you can learn this in-demand qualification and help them with addressing complex challenges.