disojn / Time-Series-EDA-and-Forecast
In this section, I begin with the excel file of sales data, which I obtained from the Tableau Community Forum. As a recall, the data contains mostly categorical variables and components of the vectors from the description column. The index column is a timeseries format. The major objective of this section is to understand the general trends in t…
☆27Updated 4 years ago
Related projects: ⓘ
- Association rule mining is a technique to identify underlying relations between different items.☆65Updated 5 years ago
- A Data Science project that uses an ARIMA model for Time Series Forecasting, to predict the temperature of any given city across a specif…☆29Updated 6 years ago
- Customer segmentation using k-means clustering in python☆55Updated 6 years ago
- The goal of this notebook is to implement and compare different approaches to predict item-level sales at different store locations.☆33Updated 2 years ago
- Interpreting Machine learning Models(ML Models,DL models) with Lime,Eli5,Shap,etc☆23Updated 2 years ago
- In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays an…☆96Updated 6 years ago
- Address imbalance classes in machine learning projects.☆35Updated 3 years ago
- The goal of this project is to build an unsupervised machine learning model that predicts customers' next purchase date.☆19Updated 3 years ago
- Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance…☆47Updated 4 years ago
- Exponential Smoothing, SARIMA, Facebook Prophet☆11Updated 3 years ago
- Time series forecasting using LSTM in Python☆80Updated last month
- Time Series Decomposition techniques and random forest algorithm on sales data☆54Updated 2 years ago
- This repository will have all the necessary files for machine learning and deep learning based Banking Churn Prediction ANN model which w…☆16Updated last year
- Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso…☆87Updated 9 months ago
- This repo contains my jupyter notebook for a data challenge for building a machine learning model to identify fraud in e-commerce transac…☆12Updated 7 years ago
- This repository contains implementation of some techniques like SMOTE, ADASYN, SMOTE + Tomek Links, SMOTE + ENN to overcome class imbalan…☆40Updated 3 years ago
- Predict seasonal item sales using classical time-series forecasting methods like Seasonal ARIMA and Triple Exponential Smoothing and curr…☆27Updated 4 years ago
- Different clustering approaches applied on different problemsets☆39Updated 4 years ago
- Lending Club Data Loan Default Prediction☆51Updated last year
- A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)☆67Updated last year
- 📈Forecasting Total amount of Products using time-series dataset consisting of daily sales data provided by one of the largest Russian so…☆55Updated 4 years ago
- Using Python StatsModel ARIMA to Forecast Time Series of Cars in Walmart Parking Lot☆29Updated 6 years ago
- Multivariate time series forecasting using the VAR Model in Python. Video Explanation available on my Youtube channel: https://www.youtub…☆23Updated 3 years ago
- Introduction In ecommerce companies like online retails, customer segmentation is necessary in order to understand customers behaviors. I…☆9Updated 4 years ago
- Using Time Series forecasting and analysis to predict Walmart Sales across 45 stores.☆20Updated 5 years ago
- Book Projects☆24Updated 3 years ago
- Small example on how you can detect multicollinearity☆13Updated 3 years ago
- Stock market prediction of a stock using stacked LSTM☆9Updated 4 years ago
- This portfolio is a compilation of notebooks which I created for Data Science related tasks like Tutorials, Exploratory Data Analysis, an…☆75Updated 7 months ago
- This machine learning model (LSTM Time Series model) helps us to forecast demand of a supply chain business problem. This model uses Kera…☆27Updated 6 years ago