Business Intelligence and Analytics 10
Friday, March 29, 2019
Business Intelligence and Analytics 10
1 Unlocking Value From Data Is Key To A Successful Digital Transformation
https://www.forbes.com/sites/markvenables/2019/03/28/unlocking-value-from-data-is-key-to-a-successful-digital-transformation/
For oil and gas digital transformation is not a project where you make a roadmap and have a defined finish line, which, once crossed, constitutes a company being digitalized. Digitalization is achieved by implementing hundreds of use cases in a scalable manner.
2 Why the biggest and best struggle to grow
https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/why-the-biggest-and-best-struggle-to-grow
The largest, most successful companies would seem to be ideally positioned to create value for their shareholders through growth. After all, they command leading market and channel positions in multiple industries and geographies; they employ deep benches of top management talent utilizing proven management processes; and they often have healthy balance sheets to fund the investments most likely to produce growth.
3 Explaining how AI works for non-coders and non-mathematicians: Introduction Part 1
https://medium.com/@nishul1/ai-for-the-rest-of-us-part-1-cfe1087918a5
There is a huge amounts of hype swirling around today about AI. There is also a huge amount of discussion about it’s impact on society today and in the future. Yet — I’ve seen very little material explaining well how an AI actually works. How is an AI built? What does it actually do inside the black box?
4 Explaining how AI works for non-coders and non-mathematicians: An Example Part 2
https://medium.com/@nishul1/ai-for-the-rest-of-us-part-2-4f3bd8ac58bd
This is part 2 of a post that is seeking to explain AI in a way anyone can understand it. Part 1 had some background and introduction. This post has an example hopefully anyone can follow!
5 Logistic Regression in One Picture
https://www.datasciencecentral.com/profiles/blogs/logistic-regression-in-one-picture
Logistic regression is regressing data to a line (i.e. finding an average of sorts) so you can fit data to a particular equation and make predictions for your data. This type of regression is a good choice when modeling binary variables, which happen frequently in real life (e.g. work or don’t work, marry or don’t marry, buy a house or rent…). The logistic regression model is popular, in part, because it gives probabilities between 0 and 1.
6 3 Easy Use-cases – bitgrit Data Science Publication
https://medium.com/bitgrit-data-science-publication/from-0-to-ai-for-marketing-hero-3-easy-use-cases-dd8efbc14cbc
You’ve heard that AI is transforming marketing, but you may not know how to separate hype from real value. I’ll cover the 3 easiest, fastest, and most profitable AI use-cases to get started with. The main business metric in each of these is Return on Marketing Investment (ROMI).
7 The Deep Learning Toolset — An Overview
https://www.kdnuggets.com/2019/03/deep-learning-toolset-overview.html
Every problem worth solving needs great tools for support. Deep learning is no exception. If anything, it is a realm in which good tooling will become ever more important over the coming years.
8 Four steps for marketers to gain consumer trust | CMO Strategy
https://adage.com/article/cmo-strategy/steps-marketers-gain-consumer-trust/317158/
For brand marketers, the continuing challenges associated with privacy and data protection are not going away. As brands develop new policies and strategies, it’s critical to recognize the necessity of protecting the relationship with the brand’s consumer base.
9 AI in Digital Marketing — the bacon that just needs to be bought and eaten?
https://medium.com/@nele.dagefoerde/ai-in-digital-marketing-the-bacon-that-just-needs-to-be-bought-and-eaten-bec22616b009
Attending this week’s AI in Marketing conference in Zurich was not only inspiring for all the new things that are out there in Digital Marketing at the moment. Also, it showed the opportunities and challenges of today’s Digital Marketing.
10 Bias Variance Trade Off – Data Science Central
https://www.datasciencecentral.com/profiles/blogs/bias-variance-trade-off
Deep Learning is a highly empirical domain which majorly focusses on fine-tuning the various parameters. The choice of these parameters defines the accuracy of the model. So, it becomes important to choose such parameters wisely.