(testing signal)

Tag: forecasting

Stanislaus State professor starts wildfire research

Stanislaus State Assistant Professor of Physics Wing To was having some beers with atmospheric scientists last year when they came up with an idea for a research project that could speed up predictions of the atmospheric effects of California wildfires. The topic of the discussion was how to change predictive modeling to produce quicker forecasts of the atmospheric effects of a wildfire before the pollution spreads over a wide area. The traditional approach requires the calculation of complex mathematical equations, but atmospheric scientists are now exploring faster modeling methods using…

To Learn AI, Should You Know Data Science?

Data Science, Machine Learning, and Artificial Intelligence are the significant drivers of the fourth industrial revolution. Since data powers all these fields, they are often used interchangeably. However, despite the similarities, Data Science, ML and AI are different from each other.
Data Science is a multidisciplinary field with a focus on the use of data to derive insights. A good data scientist must possess a wide range of skills, including programming, mathematics, and domain knowledge of the desired field of application. To analyse data, make inferences or forecast predictions,…

The Possible Great Play for Crypto in December | by Ann Inw | Nov, 2021

Consider having exposure in these two crypto sectorsI am someone who has learned to know better than predicting the market. My style has always been mostly just riding gracefully — and often failed miserably — on whichever trend we got at the moment.But once in a while, like today, I couldn’t help but be tempted to forecast the upcoming crypto trend. After all, I am somewhat experienced in this industry. When you’re here long enough — and obsessed 24/7 (yep I don’t have a day job anymore) — you’d develop more keen sense while watching stuff unravel in the market. Perhaps,…

What is Web 3.0, Really?

One of the things I learned as a researcher, interviewer, and forecaster was that most people who have acquired at least some knowledge of a given emerging technology aren’t looking at the horizon much. They tend to head down, perhaps working on just making the chosen tech work, or trying to discover new ways to make it work.
They may not have the opportunity or even the desire to build a broad, forward-looking perspective. They may not themselves be blessed with good research or due diligence habits, or a sense of how systems as a whole evolve and how the tech under focus fits into…

Improving Machine Learning: How Knowledge Graphs Bring Deeper Meaning to Data

Enterprise machine learning deployments are limited by two consequences of outdated data management practices widely used today. The first is the protracted time-to-insight that stems from antiquated data replication approaches. The second is the lack of unified, contextualized data that spans the organization horizontally.
Excessive data replication and the resulting “second-order effects” are creating enormous efficiencies and waste for data scientists in most organizations. According to IDC, over 60 zettabytes of data were produced last year, and this is forecast to increase at a CAGR…

How to Use Data Science in the Stock Market?

by Madhurjya Chowdhury
November 4, 2021
You can read about the potential of data science everywhere. Data is a source of concern for everyone. Businesses are interested in learning how data may help them cut costs and boost their profits. Data science has piqued the interest of the healthcare business, which wants to know how it may help them forecast illnesses and deliver better treatment to its patients.Data science is being utilized in this way to give an in-depth understanding of the stock market and financial statistics. We purchase, sell, and hold stocks. All of this is done in…

What’s Next for AI in the Public Sector?

PHOTO:
ElevenPhotographs | unsplash
We’ve all been hearing how almost any organization, of any size, anywhere can leverage artificial intelligence (AI) to boost productivity and revenue. Teachers can alter course material to fit the learning needs of students, insurers can grow capacity and reduce fraudulent claims, utilities can predict equipment downtime and avoid outages, consumer packaged goods (CPG) organizations can forecast what their customers will want to buy next. The applications of AI to business are endless, limited only by the fact that poor data used to train the AI can…

AI forecasts new atrial fibrillation, stroke risk

Conventional 12-lead ECGs can’t typically forecast future outcomes such as stroke, the authors noted. So, they set out to create a deep neural network to better utilize the electric signals emitted by the heart.

That included 1.6 million ECGs from 430,000 patients treated at Geisinger Health System in Danville, Pennsylvania. They specifically designed the tool to predict adverse heart events in patients with no prior history of atrial fibrillation, but who were likely to experience the potentially deadly event within 12 months.

The neural network beat out current clinical models…

Building interpretable forecasting and nowcasting models: An overview to DeepXF

Hello, friends. In this blog post, we will quickly peek through the package “Deep-XF” that is useful for forecasting, nowcasting, uni/multivariate time-series data analysis, filtering noise from time-series signals, comparing two input ts signals, etc. The USP of this package is its bunch of add-on utility helper functions, and the model explainability module that can be used for explaining model results, be it the forecasting/nowcasting problem.

Overview:-

DeepXF is an open source, low-code python library for forecasting and nowcasting problems. DeepXF helps in designing complex…

Small and Medium Sized Businesses (SMEs) Needs Self-Serve Advanced Analytics

If your small or medium-sized (SME) business is looking for ways to improve forecasting, problem-solving and market opportunities, it must have an agile, swift analytical process that will allow business users to leverage their role, their knowledge of their business function, and their collaborative initiatives to gather, analyze and share information and improve business results.
A recent Gartner report states that by 2021, natural language processing and conversational analytics will boost analytics and business intelligence adoption from 35% of employees to over 50%, including new…

Sports NFTs are popular, but are they a winning investment?

Gone are the days when a sports buff walks into a store, buys a pack of Topps trading cards and stumbles upon a one-of-a-kind baseball collectible. Today’s card collectors have shifted their attention — and dollars — to sports non-fungible tokens, or NFTs, that offer proof of unique ownership of a video, photo, audio snippet or other digital capture of an important moment in sports history

The popularity of sports NFTs has exploded in recent years, and people who sell the digital memorabilia say 2021 is just the tipoff. The entire NFT market value is forecast to grow to $75…

Coinbase CEO says NFTs could be ‘big or bigger’ than crypto trading



Coinbase Global Co-Founder Brian Armstrong says the market for non-fungible tokens (NFTs) could rival or even be larger than the company’s cryptocurrency business. That was a bold statement from Coinbase’s chief executive officer, made on a conference call on Tuesday after the largest US digital-asset exchange reported third-quarter revenue of around $1.3 billion. The declaration helped to ease concern that revenue was below forecast even after a more than fivefold increase from a year earlier.









Coinbase plans to open…

Rabobank: Our System Can Fall Apart If Every Peasant Quits The Physical Economy And Starts Trading…

By Michael Every of RabobankRevising Views and Economic GravityFriday’s US payrolls report for once proved somewhat interesting – and also underlined just how pointless a release it is via backwards revisions that dramatically shift perceptions of what the labour market is (or isn’t) doing. Headline jobs growth was 531K vs. 450K forecast, and September was revised up to 312K from 194K, and August up from 366K to 483K. The unemployment rate dropped to 4.6%, but it’s not clear if that means anything given the BLS are evidently making this all up more than usual due to Covid…

Analyst Predicts Rallies for Solana, Chiliz and Low-Cap Gaming Project, Forecasts Ideal Time To Rotate to Ethereum

A popular crypto strategist sees significant rallies ahead for Solana (SOL), Chiliz (CHZ) and a low-cap gaming project as the metaverse heats up.
The pseudonymous trader SmartContracter tells his 178,600 Twitter followers that he firmly believes SOL will reach $900 this cycle, which would represent a 275% increase from its current value of $233.
The analyst uses a Solana futures chart to show that SOL recovered from a dip more quickly than Ethereum (ETH) after each token hit new all-time highs (ATHs) this week.
“SOL once again first to recover and make ATH, couldn’t have done…

Bitcoin retests support, with trader forecasting BTC price dip to $55K


Bitcoin (BTC) denied bulls their big break on Nov. 4 as sideways action dragged the market ever closer to $60,000.BTC/USD 1-hour candle chart (Bitstamp). Source: TradingViewBTC hodlers in “buy the dip” modeData from Cointelegraph Markets Pro and TradingView showed BTC/USD back below $62,000 at 8 am UTC.The pair saw a difficult 24 hours after hitting local highs above $64,000, finally bouncing at $60,000 in a brief but significant dip. The plebs continue to stack.— Dylan LeClair …

Facebook Expects Metaverse Project Will Cost At Least $10 Billion—In 2021 Alone

SOPA Images/LightRocket via Getty Images
Mark Zuckerberg’s got the metaverse on his mind—and it’s a costly consideration.
One starting at a cost of $10 billion this year alone, according to a new forecast on profit and expenses Facebook offered up to investors in its third-quarter earnings report. And that $10 billion figure, Zuckerberg told later analysts in a conference call, will only likely increase in the years to come.

To Zuckerberg, the metaverse, a bleeding-edge…

Decentralized Identifiers Market See Huge Growth for New Normal| Authenteq Tarbena GmbH, Civic Technologies, Inc. – Puck77

Decentralized Identifiers Market report focused on the comprehensive analysis of current and future prospects of the Decentralized Identifiers industry. It describes the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth during a forecast period. An in-depth analysis of past trends, future trends, demographics,…

Forecasting with Machine Learning Models

mlforecast makes forecasting with machine learning fast & easyBy Nixtla Team.TL;DR: We introduce mlforecast, an open source framework from Nixtla that makes the use of machine learning models in time series forecasting tasks fast and easy. It allows you to focus on the model and features instead of implementation details. With mlforecast you can make experiments in an esasier way and it has a built-in backtesting functionality to help you find the best performing model.You can use…

How to Improve Deep Learning Forecasts for Time Series

Clustering its benefits.Clustering time series data before fitting can improve accuracy by ~33% — src.Figure 1: time series clustering example. Image by author.In 2021, researchers at UCLA developed a method that can improve model fit on many different time series’. By aggregating similarly structured data and fitting a model to each group, our models can specialize.While fairly straightforward to implement, as with any other complex deep learning method, we are often…

The Future of Pandemic Modeling

A hundred years of modeling didn’t help forecast the extent of the current pandemic.
Hundreds of thousands of deaths could have been prevented with better models.
The quantitative economic epidemiological model may be the future for pandemic modeling.

Many countries, including the UK and US, mounted inefficacious responses to the Covid-19 pandemic, thanks to inaccurate and delusive models. No one saw how badly the pandemic would affect social and economic constructs; WHO director General…

Reduced-Rank Vector Autoregressive Model for High-Dimensional Time Series Forecasting

IntroductionNowadays, with the remarkable development of data collection/availability techniques, we have more opportunities to approach many kinds of time series data in a lot of scientific and industrial fields. There are many types of time series data, including univariate time series, multivariate time series, and multidimensional time series. For multivariate time series, the data has more than one time-dependent variable, and each variable has dependencies on other variables….