Friday, March 1, 2019
Business Intelligence and Analytics 7
1 A beginner’s guide to Linear Regression in Python with Scikit-Learn
https://towardsdatascience.com/a-beginners-guide-to-linear-regression-in-python-with-scikit-learn-83a8f7ae2b4f?source=rss—-7f60cf5620c9—4&gi=32b13e3427c7
There are two types of supervised machine learning algorithms: Regression and classification. The former predicts continuous value outputs while the latter predicts discrete outputs. For instance, predicting the price of a house in dollars is a regression problem whereas predicting whether a tumor is malignant or benign is a classification problem.
2 3 Key Ways Big Data Is Changing Financial Trading
https://www.smartdatacollective.com/3-key-ways-big-data-is-changing-financial-trading/
Big data is one of the internet-oriented developments that have caused enormous impact across all industries over the last couple of decades. The term big data refers to the gigantic amounts of information constantly collected by websites and search engines as people continue to use the internet for diverse purposes. It consists of all kinds of data – numbers, text, images, tables, audio, video and any other possible type of information.
3 7 Jobs Humans Can Do Better Than Robots And AI
https://www.smartdatacollective.com/7-jobs-humans-can-do-better-than-robots-and-ai/
The rise of artificial intelligence or AI in the past decades has resulted in collective anxiety around the world. The common apprehension is that there will be massive loss of jobs as robots and computers eventually replace employees. The fear is not without some basis; after all, robots and computers have proven to be far better than humans at executing certain tasks. However, it must be noted that not all jobs will eventually be replaced by AI. So, what’s the secret to staying ahead and remaining employable? The answer lies in knowing both what AI is capable of doing better than humans and what humans are capable of doing better than AI.
4 3 reasons to add deep learning to your time series toolkit
https://www.oreilly.com/ideas/3-reasons-to-add-deep-learning-to-your-time-series-toolkit
The ability to accurately forecast a sequence into the future is critical in many industries: finance, supply chain, and manufacturing are just a few examples. Classical time series techniques have served this task for decades, but now deep learning methods—similar to those used in computer vision and automatic translation—have the potential to revolutionize time series forecasting as well.
5 Evolution of Automated Marketing Tools: Improving Customer Experience
https://blog.marketo.com/2019/02/continually-improving-the-customer-experience-the-evolution-of-automated-marketing-tools.html
Automated marketing tools have evolved over the last few decades, giving generations of marketers new and innovative ways to engage with their customers. That’s not going to stop anytime soon. Automated marketing technology continues to advance rapidly. And over the next few years, it’ll change the way people experience your brand and interact with your company.
6 Blockchain Post-Trade Platform Vakt Partners With Majority of North Sea Oil Market
https://cointelegraph.com/news/blockchain-post-trade-platform-vakt-partners-with-majority-of-north-sea-oil-market
Vakt, a Blockchain-based post-trade platform for oil, has signed up four new clients, according to a statement published on the platform’s website on Feb. 25.
As per Etienne Amic, Vakt’s recently appointed CEO, the company has partnered with four new clients prior to its official launch at International Petroleum Week, which starts in London today, Feb. 26.
7 5 Lead Generation Techniques for Small Businesses in 2019
https://blog.marketo.com/2019/02/5-lead-generation-techniques-for-small-businesses-in-2019.html
You’ve got a loyal following of delighted customers. Now it’s time to grow. But to do that, you need leads.
The question is, how do you go about getting them? What techniques and approaches will help you generate a consistent stream of leads this year and beyond?
8 PyTorch on Azure: Deep learning in the oil and gas industry | Blog
https://azure.microsoft.com/en-us/blog/pytorch-on-azure-deep-learning-in-the-oil-and-gas-industry/
Drilling for oil and gas is one of the most dangerous jobs on Earth. Workers are exposed to the risk of events ranging from small equipment malfunctions to entire off shore rigs catching on fire. Fortunately, the application of deep learning in predictive asset maintenance can help prevent natural and human made catastrophes.
