Create a Demand Sales Forecast Model and Minimize the Error. In this article, we’ll do a simple sales forecast model with real data and then improve it by finding relevant features using Python.
Sales or Demand Forecasts are a priority *on ahuge amount of companies (from startups to global corporations) Data Science/Analytics departments. To say the least, there is a *low supply of experts in the subject. Reducing the error even by a small amount can make a huge difference in revenue or savings.
In this article, we’ll do a simple sales forecast model with real data and then improve it by finding relevant features using Python.
For this article, we’ll use real weekly sales data provided by Walmart.
Walmart released data containing weekly sales for 99 departments (clothing, electronics, food…) in every *physical store *along with some other added features.
How to use Deep Learning for Time Series Forecasting. An application of the RNN family
In this article, we will be discussing an algorithm that helps us analyze past trends and lets us focus on what is to unfold next so this algorithm is time series forecasting. In this analysis, you have one variable -TIME. A time series is a set of observations taken at a specified time usually equal in intervals. It is used to predict future value based on previously observed data points.
Learning is a new fun in the field of Machine Learning and Data Science. In this article, we’ll be discussing 15 machine learning and data science projects.
An intuitive take on sales forecasting from traditional time series models to modern deep learning. In any company, there is an embedded desire to predict its future revenue and future sales. The basic recipe is: Collect historical data related to previous sales and use it to predict expected sales.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant