There are five types of traditional time series models most commonly used in epidemic time series forecasting, which includes
AR models express the current value of the time series linearly in…Continue
Added by Sharmistha Chatterjee on July 26, 2020 at 7:09am — No Comments
Milvus aims to achieve efficient similarity search and analytics for massive-scale vectors. A standalone Milvus instance can easily handle vector search for billion-scale vectors. However, for 10 billion, 100 billion, or even larger datasets, a Milvus cluster is needed. The cluster can be used as a standalone instance for upper-level applications and can meet the business needs of low latency, high concurrency for massive-scale data. A Milvus cluster can resend requests, separate reading…Continue
Added by Kate Shao on July 24, 2020 at 9:30pm — No Comments
Coronavirus pandemic is stretching the healthcare operational resources to an immense extent. During such a brief duration of time, COVID—19 has become one of the biggest challenges that humanity has to face in the twenty-first-century world. Many complications surround this pandemic regarding the …Continue
Added by Naveen Chandra Joshi on July 24, 2020 at 5:41am — No Comments
Traditional vs Deep Learning Algorithms in the Telecom Industry — Cloud Architecture and Algorithm Categorization
Google Cloud Architecture for Machine Learning Algorithms in the Telecom Industry
The unprecedented growth of mobile devices, applications, and services have placed the utmost demand on mobile and wireless networking infrastructure. Rapid research…Continue
Added by Sharmistha Chatterjee on July 23, 2020 at 8:26pm — No Comments
Here is our selection of featured technical resources and articles posted since Monday:
Added by Vincent Granville on July 23, 2020 at 1:30pm — No Comments
I can't find anymore where this chart, featuring relations between distributions, was first published. I remember seeing it on the Cloudera blog.
Another shorter one featuring the most useful one for statistical analysis, can be found…Continue
In the era of the Internet, the ability to crunch large amounts of data and process it with speed and efficiency has become essential for businesses to survive. But you try sitting down and going through all that data by hand: you'll get done sometime in the year 2050 if you're lucky.
That's where machine learning comes to the rescue. But…Continue
Added by Or Hillel on July 22, 2020 at 9:59pm — No Comments
Earlier this week, I was speaking at an event on AI for Real Estate where I showed an example from a BBC clip which said that “central London is now a ghost town” (due to COVID 19)
A few months ago, this headline would have been laughable
In London, central London and the London underground are a key fabric of daily…Continue
Added by ajit jaokar on July 22, 2020 at 2:00pm — No Comments
This article was written by Stephanie Kim.
Recently I gave a talk at PyData Seattle about how to ramp up your data science skills by borrowing tips and tricks from the developer community. These suggestions will help you become a more proficient data scientist who is loved by your team members and stakeholders.
This post is broken up into…Continue
Added by Andrea Manero-Bastin on July 21, 2020 at 9:00am — No Comments
Mike Romeri, CEO
During the current COVID-19 pandemic, virtually all companies have faced significant changes in demand. Some companies have seen significant increases (e.g., grocery chains, packaged food companies), and others have seen their revenue drop to unsustainable levels (e.g., air travel, hospitality, automotive). Still others have seen both outcomes if they serve different industry segments with very different levels of end-user demand.
There is much talk of AI automation of many critical business processes over the next decade as the technology matures. Management and workers throughout organizations are wondering, “Where does that leave me and my job?” With so much focus on the technology of artificial intelligence, the question of human/machine working relationships and learn- ing has received relatively short…
Added by Betsy Romeri on July 21, 2020 at 4:30am — No Comments
This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes.
Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the…Continue
Added by Ram Alagianambi on July 20, 2020 at 9:00pm — No Comments
As a data scientist, have you ever been frustrated that your stakeholders don’t see the value that you bring to the table? You may ask yourself, “How far should I go in explaining the work I do or what my models are doing?” If that sounds like you, then pay close attention to this post and the next, as they are all about improving collaboration between data scientists and other stakeholders.
This is a two-part post: This article…Continue
Added by Ram Alagianambi on July 20, 2020 at 8:30pm — No Comments
Summary: Advances in very low cost compute and Model Based Reinforcement Learning make this modeling technique that much closer to adoption in the practical world.
Added by William Vorhies on July 20, 2020 at 12:30pm — No Comments
Over the last couple of years, there has been a lot of hype around robotic process automation. This makes a lot of sense if you consider that in 2018 Gartner was already labeling it “…Continue
Added by Daniel Pullen on July 20, 2020 at 4:30am — No Comments
Added by Vincent Granville on July 19, 2020 at 4:00pm — No Comments
Time Series forecasting in PBI is based on the thumb technique of smoothening time series prediction called Exponential Smoothening (ES). ES of time series data assigns exponentially decreasing weights for newest to oldest observations. ES is also be used for time series with trend and seasonality. This model is usually used to make short term forecasts, as longer-term forecasts using this technique can be quite unreliable. Collectively, the methods are sometimes referred to as ETS models,…Continue
Added by Vigneswaran S on July 19, 2020 at 1:01am — No Comments
Blockchain technology is the talk of the techno-world. The technology is booming at a faster rate and is promising for almost all industries as it conforms trust relations in the techno-world. Blockchain builds a trusted network through its encryption algorithms and accounts for controllable permissions, provenance, transactions, smart contracts, and many applications.…Continue
Added by Aileen Scott on July 16, 2020 at 7:00pm — No Comments
Here is our selection of featured articles and technical resources posted since Monday:
Added by Vincent Granville on July 16, 2020 at 12:30pm — No Comments
Added by Hadley Christoffels on July 16, 2020 at 8:00am — No Comments