Statistical forecasting | Time series
Forecasting is the process of making predictions based on past and present data. Later these can be compared (resolved) against what happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results. Prediction is a similar, but more general term. Forecasting might refer to specific formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods or the process of prediction and resolution itself. Usage can vary between areas of application: for example, in hydrology the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period. Risk and uncertainty are central to forecasting and prediction; it is generally considered a good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible. In some cases the data used to predict the variable of interest is itself forecast. (Wikipedia).
Time Series Forecasting on Stock Prices
Watch this talk to learn how to set up a process for stock price forecasting using Python and Machine Learning. PUBLICATION PERMISSIONS: Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=72g4V6Ucnlc
From playlist Python
Time Series Forecasting in Minutes
In this Data Science in Minutes, we will describe what time series forecasting is, and provide several examples of when you can use time series for your data. Time series forecasting is looking at data over time to forecast or predict what will happen in the next time period, based on patt
From playlist Data Science in Minutes
Introduction: Data Sciences for Climate and Environment
This is a short introduction to the Data Sciences for Climate and Environment by Professors Richard Smith and Mark Girolami. You can view the full event here: https://www.youtube.com/playlist?list=PLuD_SqLtxSdUVT_2SSPzZSC__kAxpkm8w About the event Collectively, we are modelling and moni
From playlist Data Sciences for Climate and Environment
Panel: Data Sciences for Climate and Environment
You can view the full event here: https://www.youtube.com/playlist?list=PLuD_SqLtxSdUVT_2SSPzZSC__kAxpkm8w This is a a video of the Data Sciences for Climate and Environment panel discussion. This segment involved all of the featured speakers and concluded the event. About the event Col
From playlist Data Sciences for Climate and Environment
Find out how DeepMind is working to improve “nowcasting” – https://www.deepmind.com/blog/nowcasting-the-next-hour-of-rain – and learn more about their scholarship program – https://www.deepmind.com/scholarships There are two types of rain, and one of them is almost impossible to forecast
From playlist Atmospheric Science
Probabilistic Forecasting in TimeSeries
More info + to join: https://community.ai.science/time-series-forecasting
From playlist Mega Meetup VIII
What Can't We Predict With Math?
Solar eclipses are fairly predictable, but the behavior of the stock market over the next couple days...not so much. But why? Is any given problem simply a matter of having a big enough computer and a complex enough algorithm to solve it, or are there certain things that lie beyond the rea
From playlist Technology
Lecture7. Time series forecasting
Data Science for Business. Lecture 7 slides: https://drive.google.com/file/d/17Fn0uhOVs4I8T1ut2BWM4OY1a8M9nzMk/view?usp=sharing
From playlist Data Science for Business, 2022
Basic Excel Business Analytics #54: Basic Forecasting Methods & Measures of Forecast Error
Download files: https://people.highline.edu/mgirvin/AllClasses/348/348/AllFilesBI348Analytics.htm Learn about some Basic Forecasting Methods: 1) (00 Intro to Time Series and Forecasting 2) (02:10) Naïve Method or Most Recent Method for Forecasting 3) (04:34) Forecast Error and Mean Foreca
From playlist Excel Business Analytics (Forecasting, Linear Programming, Simulation & more) Free Course at YouTube (75 Videos)
Darts For Time Series Forecasting (Python Library for Forecasting)
This talk will give an introduction to Darts (https://github.com/unit8co/darts), an open-source library for time series processing and forecasting. Darts provides a wide variety of models and tools under a unified and user-friendly API. We will give a high level introduction to both time s
From playlist Machine Learning
Multi-decadal Variability, Climate Change, and Indian Monsoon (Lecture 13) by B N Goswami
ICTS Summer Course 2022 (www.icts.res.in/lectures/sc2022bng) Title : Introduction to Indian monsoon Variability, Predictability, and Teleconnections Speaker : Professor B N Goswami (Cotton University) Date : 23rd April onwards every week o
From playlist Summer Course 2022: Introduction to Indian monsoon Variability, Predictability, and Teleconnections
Balance and tropical data assimilation - Nedjeljka Zagar
Balance and tropical data assimilation Nedjeljka Zagar, U.Ljubljana, Slovenia. DISCUSSION MEETING: MATHEMATICAL PERSPECTIVES ON CLOUDS, CLIMATE, AND TROPICAL METEOROLOGY THURSDAY, 25 JANUARY, 2013
From playlist Mathematical Perspectives on Clouds, Climate, and Tropical Meteorology
Forecast Sales Performance in Excel
If you like this video, drop a comment, give it a thumbs up and consider subscribing here: https://www.youtube.com/c/HowToBeAnAdult?sub_confirmation=1 Music from: YouTube Audio Library Check out our new project: https://magnimetrics.com Automated Financial Analysis. Reinvented. Follow m
From playlist Excel Tutorials
Why Is the Weather So Hard to Predict?
If you think the weather forecast is always wrong, well then we’ve got news for you. In Part 1 of this series about the weather, Julian explains everything you need to know about predicting the forecast and why it’s inherently a chaotic mess of math and hailstorms. » Subscribe to Seeker+!
From playlist Seeker+
sktime - A Unified Toolbox for ML with Time Series
This tutorial is about sktime - a unified framework for machine learning with time series. sktime features various time series algorithms and modular tools for pipelining, ensembling and tuning. You will learn how to use, combine and evaluate different algorithms on real-world data sets an
From playlist Python
A solar system, a simulation made with Excel
An Excel simulation of the solar system. You can see how things are recursively computed: the mutual gravity force from the locations, the accelerations, the velocities, and finally the updated locations. The solar eclipse is also shown. This is clip is intended to illustrate Chapter 24 Ap
From playlist Physics simulations
Data-driven and data-augmented modeling of chaotic spatiotemporal dynamical system by Jaideep Pathak
DISCUSSION MEETING NEUROSCIENCE, DATA SCIENCE AND DYNAMICS (ONLINE) ORGANIZERS: Amit Apte (IISER-Pune, India), Neelima Gupte (IIT-Madras, India) and Ramakrishna Ramaswamy (IIT-Delhi, India) DATE : 07 February 2022 to 10 February 2022 VENUE: Online This discussion meeting on Neuroscien
From playlist Neuroscience, Data Science and Dynamics (ONLINE)