Friday, November 8, 2019
Business Intelligence and Analytics 37
1 Data Cleaning and Preprocessing for Beginners
https://www.kdnuggets.com/2019/11/data-cleaning-preprocessing-beginners.html
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. //Wikipedia
2 3 Lies Data Scientists Tell Themselves
https://towardsdatascience.com/3-lies-data-scientists-tell-themselves-8d29af9ccdf2
If you browse r/MachineLearning you’ve probably seen some posts over the last couple weeks about Siraj Raval, a YouTube personality working to build a name for himself as an online data science educator. He’s recently been under fire for plagiarism, exaggeration of his skills, and milking the data science hype for a quick buck.
3 Understanding Boxplots
https://www.kdnuggets.com/2019/11/understanding-boxplots.html
The image above is a boxplot. A boxplot is a standardized way of displaying the distribution of data based on a five number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.
4 Research Guide: Advanced Loss Functions for Machine Learning Models
https://www.kdnuggets.com/2019/11/research-guide-advanced-loss-functions-machine-learning-models.html
In addition to good training data and the right model architecture, loss functions are one of the most important parts of training an accurate machine learning model. For this post, I’d love to give developers an overview of some of the more advanced loss functions and how they can be used to improve the accuracy of models—or solve entirely new tasks.
5 Protecting Data Privacy in the Era of Digital Trading
https://insidebigdata.com/2019/11/08/protecting-data-privacy-in-the-era-of-digital-trading/
Technology has made it easier for anyone to invest their money. From automated trading advice and recommendations to wide access to global markets, even a novice investor can begin trading or market speculation with little money or experience. This has created an explosion of capital around the world.
6 Manufacturing Industry Reshuffle — Will Companies Thrive or Barely Survive in The New Era of AI-Defined Automation?
https://towardsdatascience.com/manufacturing-industry-reshuffle-will-companies-thrive-or-barely-survive-in-the-new-era-of-aa06a3cade5c
Previously we talked about how AI can enable robots to perform tasks that could not be done in the past. Specifically, AI robots have achieved breakthroughs in three major areas. But what impact will it have on the current landscape of the manufacturing industry? Who will be able to grasp the opportunities brought about by the new technology? Which companies will face unprecedented challenges?
7 Shaped by AI, the Future of Work Sees Soft Skills & Creativity as Essential
https://martechseries.com/mts-insights/guest-authors/shaped-ai-future-work-sees-soft-skills-creativity-essential/
As technology advances, it disrupts and revolutionizes entire business sectors, often making our jobs easier and our lives better. And while we don’t always know the full impact of such technological advancement, with Artificial Intelligence (AI) it’s becoming increasingly clear that AI will disrupt nearly every industry in one way or another.
8 4 Important Things Universities Need to Teach About Data Science/Analytics
https://towardsdatascience.com/4-important-things-universities-need-to-teach-about-data-science-analytics-6ab5988639ca
I remembered the analytics and machine learning projects I did as an undergraduate, the professors would expect us to produce presentations and scientific reports by implementing statistical and machine learning concepts taught in class on the final few weeks of the semester. These projects have one thing in common: We are to choose readily available data sets.
9 Explainer: World’s biggest trade pact shapes up without India
https://www.reuters.com/article/us-asean-summit-trade-explainer-idUSKBN1XF0XY
Although India pulled out at the last minute, China and 14 other countries agreed in Bangkok this week on plans for what could become the world’s biggest trade agreement – the Regional Comprehensive Economic Partnership (RCEP).
10 Fatigue Can Be as Dangerous as Drinking on the Job
https://www.business2community.com/workplace-culture/fatigue-can-be-as-dangerous-as-drinking-on-the-job-02256079
Beep. Beep. Beep. Hear that? It’s your alarm sounding, except you feel like you just closed your eyes moments ago. Coming from the world of insurance, we’re surrounded by risk management best practices, and making sleep a priority for our employees and our clients has become an absolute necessity. There are more risks associated with fatigue than many realize.
