- Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model - Dec 27, 2021.
Review this detailed tutorial with code and revisit the decades-long old problem using a democratized and interpretable AI framework of how precisely can we anticipate the future and understand its causal factors?
Data Exploration, Explainable AI, Feature Engineering, Forecasting
- Avoid These Mistakes with Time Series Forecasting - Dec 2, 2021.
A few checks to make before training a Machine Learning model on data that could be random.
Forecasting, Mistakes, Python, Time Series
- Top 5 Time Series Methods - Nov 1, 2021.
Data that varies in time can offer powerful applications and use cases for data scientists to analyze. This overview considers the top techniques you can learn to understand and gain insight from time-series data.
Forecasting, Seasonality, Time Series
- Multiple Time Series Forecasting with PyCaret - Apr 27, 2021.
A step-by-step tutorial to forecast multiple time series with PyCaret.
Forecasting, Machine Learning, PyCaret, Python, Time Series
- Want To Get Good At Time Series Forecasting? Predict The Weather - Apr 20, 2021.
This article is designed to help the reader understand the components of a time series.
Forecasting, Prediction, Time Series, Weather
- Forecasting Stories 5: The story of the launch - Feb 18, 2021.
New products forecasting can be very difficult - there is no history to start with, and hence no base line. The number of assumptions can be huge. The best way to forecast then, is to try parallel approaches, build different views and triangulate on a common range.
Analytics, Business, Forecasting
- Backcasting: Building an Accurate Forecasting Model for Your Business - Feb 5, 2021.
This article will shed some light on processes happening under the roof of ML-based solutions on the example of the business case where the future success directly depends on the ability to predict unknown values from the past.
Business, Forecasting, Modeling
- Forecasting Stories 4: Time-series too, Causal too - Jun 1, 2020.
This article is about the story of taking effective business decisions basis a combined model. Let us together study how these components work hand in hand.
Causality, Forecasting, Time Series
- Outbreak Analytics: Data Science Strategies for a Novel Problem - Apr 30, 2020.
You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?
Alteryx, Coronavirus, COVID-19, Data Science, Data Visualization, Forecasting
- LSTM for time series prediction - Apr 27, 2020.
Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.
Deep Learning, Forecasting, LSTM, Neural Networks, Recurrent Neural Networks, Time Series
- Forecasting Stories 2: The Power of a Seasonality Index - Apr 14, 2020.
Read this second entry in a series on time series analysis and seasonality, and see how, through 2 simple use cases, the power of a seasonality index is uncovered.
Forecasting, Seasonality, Time Series
How (not) to use Machine Learning for time series forecasting: The sequel - Mar 30, 2020.
Developing machine learning predictive models from time series data is an important skill in Data Science. While the time element in the data provides valuable information for your model, it can also lead you down a path that could fool you into something that isn't real. Follow this example to learn how to spot trouble in time series data before it's too late.
Forecasting, Machine Learning, Mistakes, Time Series
- Predicting the President: Two Ways Election Forecasts Are Misunderstood - Mar 27, 2020.
With election cycles always seeming to be in season, predictions on outcomes remain intriguing content for the voting citizens. Misinterpretation of election forecasts also runs rampant, and can impact perceptions of candidates and those who post these predictions. A better fundamental understanding of probability can help improve our collective notion of futurism, and how we monitor elections.
Elections, Forecasting, Mistakes, Politics, Prediction
- Forecasting Stories: Is it seasonality or not? - Mar 17, 2020.
Kicking off with a series of forecasting stories, starting with seasonality and its business applications. This first article speaks of course corrections that were based on weather and calendar driven seasonality.
Forecasting, Seasonality, Time Series
- Stock Market Forecasting Using Time Series Analysis - Jan 9, 2020.
Time series analysis will be the best tool for forecasting the trend or even future. The trend chart will provide adequate guidance for the investor. So let us understand this concept in great detail and use a machine learning technique to forecast stocks.
Analysis, Finance, Forecasting, Stocks, Time Series
- Detecting stationarity in time series data - Aug 20, 2019.
Explore how to determine if your time series data is generated by a stationary process and how to handle the necessary assumptions and potential interpretations of your result.
Forecasting, Stationarity, Time Series
- A Data Scientist’s Path to Understanding Market Simulation - Jul 1, 2019.
Made possible by recent advances in computing power and machine learning, market simulation employs agent-based modeling, behavioral science and network science to recreate the complex dynamics and rules of how a population of people in a given market behave, influence each other and make decisions.
Forecasting, Market Analytics, Market Forecast, Simulation
- 6 Industries Warming up to Predictive Analytics and Forecasting - May 22, 2019.
Here are six sectors that are realizing how beneficial predictive analytics could be, embracing the possibilities of valuable insights extracted from such technology.
Forecasting, Industries, Predictive Analytics
How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls - May 10, 2019.
We outline some of the common pitfalls of machine learning for time series forecasting, with a look at time delayed predictions, autocorrelations, stationarity, accuracy metrics, and more.
Forecasting, Machine Learning, Mistakes, Stationarity, Time Series
- How To Fine Tune Your Machine Learning Models To Improve Forecasting Accuracy - Jan 23, 2019.
We explain how to retrieve estimates of a model's performance using scoring metrics, before taking a look at finding and diagnosing the potential problems of a machine learning algorithm.
Cross-validation, Forecasting, Machine Learning, Overfitting, Time Series
- An End-to-End Project on Time Series Analysis and Forecasting with Python - Sep 3, 2018.
Time series are widely used for non-stationary data, like economic, weather, stock price, and retail sales in this post. We will demonstrate different approaches for forecasting retail sales time series.
Forecasting, Python, Time Series, Trend Detection
- Data Science Predicting The Future - Jun 19, 2018.
In this article we will expand on the knowledge learnt from the last article - The What, Where and How of Data for Data Science - and consider how data science is applied to predict the future.
Data Science, Forecasting, Machine Learning, Programming Languages, Regression
- Sales forecasting using Machine Learning - May 8, 2017.
SpringML inviting business and sales leaders to its Man vs Machine Forecasting Duel - give them a day with your data and they will provide an algorithm based, unbiased forecast.
Forecasting, Machine Learning, Sales, SpringML
- Introduction to Forecasting with ARIMA in R - Jan 16, 2017.
ARIMA models are a popular and flexible class of forecasting model that utilize historical information to make predictions. In this tutorial, we walk through an example of examining time series for demand at a bike-sharing service, fitting an ARIMA model, and creating a basic forecast.
ARIMA, Datascience.com, Forecasting, R, Stationarity, Time Series
- XLMiner solves Big Data Problems in Excel - Jun 26, 2014.
XLMiner, a part of Analytic Solver Platform integrated software for predictive and prescriptive analytics - forecasting, data mining, optimization and simulation, lets you solve small or Big Data problems in Excel.
Data Mining, Excel, Forecasting, Optimization, XLMiner
