Jul2019 Aug Opinions
All (66) | Courses, Education (1) | Meetings (4) | News (5) | Opinions (18) | Top Stories, Tweets (7) | Tutorials, Overviews (30) | Webcasts & Webinars (1)
- Proptech and the proper use of technology for house sales prediction
- Aug 22, 2019.
Using the ATTOM dataset, we extracted data on sales transactions in the USA, loans, and estimated values of property. We developed an optimal prediction model from correlations in the time and status of ownership as well as the time of the year of sales fluctuations.
- Poll: Which skills / knowledge areas do you currently have, and which do you want to add or improve?
- Aug 22, 2019.
New KDnuggets survey looks to find out what skills our readers currently use, and which they are looking to add or improve. Take a few minutes to participate.
- Gender Diversity in AI Research
- Aug 21, 2019.
Through an analysis of 1.5M papers from arXiv, this study reviews the evolution of gender diversity across disciplines, countries, and institutions as well as the semantic differences between AI papers with and without female co-authors.
- Crafting an Elevator Pitch for your Data Science Startup
- Aug 19, 2019.
If you are launching a data science startup, these tips will give you a head start as you seek capital for seed funding or your next level of growth.
- Manual Coding or Automated Data Integration – What’s the Best Way to Integrate Your Enterprise Data?
- Aug 19, 2019.
What’s the best way to execute your data integration tasks: writing manual code or using ETL tool? Find out the approach that best fits your organization’s needs and the factors that influence it.
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How to Become More Marketable as a Data Scientist
- Aug 16, 2019.
As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019. - How Concerned Should You be About Predictor Collinearity? It Depends…
- Aug 15, 2019.
Predictor collinearity (also known as multicollinearity) can be problematic for your regression models. Check out these rules of thumb about when, and when not, to be concerned.
- Domain-Specific Language Processing Mines Value From Unstructured Data
- Aug 14, 2019.
Processing unstructured text data in real-time is challenging when applying NLP or NLU. Find out how Domain-Specific Language Processing can also help mine valuable information from data by following your guidance and using the language of your business.
- Statistical Modelling vs Machine Learning
- Aug 14, 2019.
At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.
- The Easy Way to Do Advanced Data Visualisation for Data Scientists
- Aug 13, 2019.
Creating effective data visualisations is a core skill for data scientists. This tutorial will guide you through how to easily develop interactive visualisations using the Python library plotly.
- How Creating an AI Study Group Boosted My Skills and Got Me a Job
- Aug 13, 2019.
The amount of time I had to put in to organize the AI Society left me sometimes sleep-deprived but it was definitely worth it. It was also one of the main factors why I got the job in Machine Learning after all. I hope that this article will inspire you to create your own AI study group!
- 6 Key Concepts in Andrew Ng’s “Machine Learning Yearning”
- Aug 12, 2019.
If you are diving into AI and machine learning, Andrew Ng's book is a great place to start. Learn about six important concepts covered to better understand how to use these tools from one of the field's best practitioners and teachers.
- 12 NLP Researchers, Practitioners & Innovators You Should Be Following
- Aug 12, 2019.
Check out this list of NLP researchers, practitioners and innovators you should be following, including academics, practitioners, developers, entrepreneurs, and more.
- Data Science: Scientific Discipline or Business Process?
- Aug 8, 2019.
Simply put, data science is an attempt to understand given data using the scientific method. That's why data science is a scientific discipline. You are free (and encouraged!) to apply data science to business use cases, just as you are encouraged to apply it to many other domains.
- Machine Learning is Happening Now: A Survey of Organizational Adoption, Implementation, and Investment
- Aug 5, 2019.
This is an excerpt from a survey which sought to evaluate the relevance of machine learning in operations today, assess the current state of machine learning adoption and to identify tools used for machine learning. A link to the full report is inside.
- Getting Started With Data Science
- Aug 5, 2019.
Over the past many months, I’ve received hundreds of messages from people asking me how they could get started with Data Science. Therefore, I thought it would be useful to write down a framework for those wanting to get started with Data Science.
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What 70% of Data Science Learners Do Wrong
- Aug 2, 2019.
Lessons learned from repeatedly smashing my head with a 2-meter long metal pole for a college engineering course. - How a simple mix of object-oriented programming can sharpen your deep learning prototype
- Aug 1, 2019.
By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.
