Any time you simplify data using a summary statistic, you lose information. Model accuracy is no different. When simplifying your model’s fit to a summary statistic, you lose the ability to determine where your performance is lowest/highest and why.
Read MoreTag: Forecasting
Feature selection for forecasting algorithms
Features are not guaranteed to improve forecast performance. In this article we explain why, and how to perform feature selection. In this article, we talk feature selection for forecasting. We start by explaining why you should think twice before adding features to your forecasts; then we talk about some ways to do feature selection for forecasting models. To put things in practical terms, we demo a feature selection method that has a decent balance between performance and computational cost in R.
Read MoreThe future of Artificial Intelligence in Weather Forecasting
Today’s weather forecasts are generated by some of the world’s most sophisticated computers. As you may know, weather forecasts are very unpredictable. This is because the climate is a very complex and volatile phenomenon that requires a great amount of money, data, and time to evaluate. The future may follow a very different path regarding weather forecasting: and that future is A.I.
Read MoreForecast Raises $19 Million to Reimagine Project Based Work Using AI-Native Technology
Forecast, the leading AI-native platform for project and resource management, announces that it has raised $19M in Series A funding.
Read MoreLinkedIn open-sources Greykite, a library for time series forecasting
For example, LinkedIn says that Silverkite improved revenue forecasts for 1-day ahead and 7-day ahead, as well as Weekly Active User forecasts for 2-week ahead. Median absolute percent error for revenue and Weekly Active User forecasts grew by more than 50% and 30%, respectively.
Read MoreThe most effective AI-Generated forecasts should be augmented by Human Insight
Every day, specialized algorithms, more commonly known as Artificial Intelligence (AI), are applied to more and more fields with tremendous effect, and the CPG industry is no different. Our clients witness it every day, as Unioncrate’s AI-generated forecasts provide them with the agility they need to stay ahead of demand in all situations.
Read MoreHow to encode Time-Series into Images for Financial Forecasting using Convolutional Neural Networks
Within forecasting there’s an age old question, ‘is what I am looking at a trend?’ Within the realm of statistics there are many tools that, with various degrees of success, answer said question. Yet, no approach has been able to achieve that which started the field of data forecasting in the first place. Looking at a graph derived from the data and drawing conclusions from it. However, thanks to Deep Learning and Artificial Neural Networks that is about to change. Welcome Computer Vision!
Read MoreThe most Feature-Rich ML forecasting methods available: Compliments of RemixAutoML
This is my go-to method. The main difference between the CatBoost, XGBoost, and H2O versions relate to the ML parameters available for tuning. All functions listed in this blog have working examples in the GitHub README, the R help files (which can be opened in your R session) or the package reference manual.
Read MoreInformer: LSTF (Long Sequence Time-Series Forecasting) Model
Time series forecasting is the most complex technique to solve and forecast with the help of traditional methods of using statistics for time series forecasting the data. But now as the neural network has been introduced and many CNN-based time series forecasting models have been developed, you can see how accurate and easy it became to predict future values based on historical time-series data points. Long short term memory(LSTM) is the one which is used for long-term forecasting. But there are many problems with LSTM which leads to further research in LSTF…
Read MoreGuide to Pytorch Time-Series Forecasting
Now PyTorch is capable of handling a full pipeline in deep learning and AI projects, but some of the things can be pretty messy like using PyTorch for Forecasting, so a third party is introduced by Jan Beitner Pytorch Forecasting”
Read MoreUnderstanding and Forecasting Customer Lifetime Value (CLTV)
While it is important to measure and track the actual CLTV from the existing customer base, a company also need to be able to estimate the CLTV for both existing and prospect customers over the extended period. There are a few things you will need to consider while predicting the CLTV.
Read MoreGoogle updates COVID-19 forecasting models with longer time horizons and new regions
In August, in partnership with the Harvard Global Health Institute, Google launched a set of models — the COVID-19 Public Forecasts — that provide projections of COVID-19 cases, deaths, ICU utilization, ventilator availability, and other metrics for U.S. counties and states. Today, the two organizations released what they claim are significantly improved models — trained on public data from Johns Hopkins University, Descartes Labs, the United States Census Bureau, and elsewhere — that expand beyond the U.S.
Read MoreTop 10 AI trends to watch in 2021
The global AI market size was calculated as $39.9 Billion in 2019 and expected to achieve compound annual growth rate (CAGR) up to 42.2% from 2020 to 2027. Technology has made innovations in big fields like healthcare, retail, automobile, and finance with continuous research. We have come up with Top 10 Artificial Intelligence Trends to watch in year 2021. These have the potential to hit great innovation in future. Let’s have a look at these strategies:
Read MoreScaling your Time Series Forecasting project
For our system to scale and accommodate more features, more models and eventually more forecasters we divided it to the above building blocks. Each building block stands on its own but also knows how to communicate and work with others.
Read MoreSktime: a unified Python Library for Time Series Machine Learning
The “sklearn” for time series forecasting, classification, and regression. Solving data science problems with time series data in Python is challenging.
Read MoreFor the International Day of Conscience, some food for thought!
We should not be creating conscious, humanoid agents but an entirely new sort of entity, rather like oracles, with no conscience, no fear of death, no distracting loves and hates. International Day of Conscience 2020.
Read MoreAI for business – Finance Office
Exploring the case for AI for business – Finance Office; budgeting, planning, forecasting and continuous accounting.
Read MoreArtificial Intelligence for Finance
Budget, Planning and Forecasting (BP&F) using Artificial Intelligence (AI). Artificial Intelligence for Finance strategically enhances and expands our management tools, artificial Intelligence and predictive analytics.
Read MoreWhitepaper: Artificial Intelligence & Finance
Artificial Intelligence or “AI” offers an unprecedented ability to improve the accuracy and predictability of Budgeting, Planning and Forecasting (BP&F). This is able to reduce the expensive and time intensive exercise of the annual budgeting process.
Read More