Friday, May 24, 2019
Business Intelligence and Analytics 18
1 Will the Real AI Please Stand Up?
https://www.informationweek.com/big-data/ai-machine-learning/will-the-real-ai-please-stand-up/a/d-id/1334670
Make sure that your use of machine learning has more substance than hype. Here’s a framework you can use to help you cut through the noise.
2 Will Programmers Have a Job in the Future? – Future Trends & Prediction
https://medium.com/future-trends-prediction/will-programmers-have-a-job-in-the-future-13b930555f5f
We’ve ushered into the age of technology, and if programming was considered in the 60s and 70s a “geek activity,” today it has become one of the most respectable, high-paying jobs one could get. It is also a sector that is rapidly evolving, and almost everything that has recently been associated with progress has also been associated with programming. That’s great. But programmers are no less susceptible than everyone else when it comes to losing their jobs. In this article, we ask the question, “will programmers still have a job in the future?”
3 Customer Success Leading Indicators and 3 Ways to Turn Around a Failing Product
https://www.business2community.com/product-management/customer-success-leading-indicators-and-3-ways-to-turn-around-a-failing-product-02199901
In the world of SaaS products, there are plenty of ups and downs. Every product goes through the process of checks and balances, and sometimes there are more downs than ups. Just because you have a ‘failing’ product doesn’t mean it’s time to pack up shop. Instead, this could be the perfect opportunity to revamp and refocus your go-to-market strategy. If your product is struggling to keep up with industry demands, it’s time to seek help from the audience that is working with your product every single day: your customers.
4 Building Digital-Ready Culture in Traditional Organizations
https://sloanreview.mit.edu/article/building-digital-ready-culture-in-traditional-organizations/
Even though traditional companies find much to admire and learn from in the cultures of born-digital companies, some born-digital qualities are cause for concern. Amazon.com, for instance, launches new businesses quickly and drives repeated efficiency gains in operations. However, it is less admired for what can be seen as uncompromising relationships with publishers, partners, localities, and workers. Uber is revered for its ability to innovate services with agility.
5 Why Location and Demographic Data Play an Essential Role in Predictive
https://datafloq.com/read/location-demographic-data-essential-role-marketing/6395
For most of the past century, marketing was far more of an art than a science. Marketers made decisions primarily off of intuition. Their models have shifted markedly in recent years, as big data plays a more important role in customer outreach and engagement. Predictive analytics is taking data-driven marketing to the next level.
6 6 Industries Warming up to Predictive Analytics and Forecasting
https://www.kdnuggets.com/2019/05/6-industries-warming-up-predictive-analytics-forecasting.html
Predictive analytics and forecasting tools help companies have more confidence about what to anticipate for the future instead of just taking educated guesses and hoping for the best.
7 A Complete Machine Learning Walk-Through in Python: Part One
https://towardsdatascience.com/a-complete-machine-learning-walk-through-in-python-part-one-c62152f39420
Putting the machine learning pieces together
Reading through a data science book or taking a course, it can feel like you have the individual pieces, but don’t quite know how to put them together. Taking the next step and solving a complete machine learning problem can be daunting, but preserving and completing a first project will give you the confidence to tackle any data science problem. This series of articles will walk through a complete machine learning solution with a real-world dataset to let you see how all the pieces come together.
8 A Complete Machine Learning Walk-Through in Python: Part Two
https://towardsdatascience.com/a-complete-machine-learning-project-walk-through-in-python-part-two-300f1f8147e2
Model Evaluation and Selection
As a reminder, we are working on a supervised regression task: using New York City building energy data, we want to develop a model that can predict the Energy Star Score of a building. Our focus is on both accuracy of the predictions and interpretability of the model.
9 Price Forecasting: Applying Machine Learning Approaches to Electricity, Flights, Hotels, Real Estate, and Stock Pricing
https://www.altexsoft.com/blog/business/price-forecasting-machine-learning-based-approaches-applied-to-electricity-flights-hotels-real-estate-and-stock-pricing/
When you give customers advice that can help them save some money, they will pay you back with loyalty, which is priceless. Interesting fact: Fareboom users started spending twice as much time per session within a month of the release of an airfare price forecasting feature. This tool continues to grow conversion for our partner.
10 5 Step Guide to Successfully Implementing Robotic Process Automation
https://www.business2community.com/product-management/5-step-guide-to-successfully-implementing-robotic-process-automation-02201465
Robotic Process Automation has been around for quite some time and is starting to gain momentum in large corporations as they’ve seen the results of cost savings from previous RPA implementations. In this article, we aim to break down what RPA is and how enterprises can go about formulating the right RPA implementation strategy from creating the business case to the initial discovery workshops and implementation to testing, and rollout.
