retentioneering-tools
Contactless-Attendance-System
| retentioneering-tools | Contactless-Attendance-System | |
|---|---|---|
| 1 | 2 | |
| 763 | 29 | |
| 1.3% | - | |
| 5.9 | 0.0 | |
| 5 months ago | 12 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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retentioneering-tools
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My Favorite Off-the-Shelf Data Science Repos, What Are Yours?
Here are my top off-the-shelf data science models for Marketing. Would be interested which other marketing data science tools you use?
Product Recommendation on Your Website with Metarank (https://github.com/metarank/metarank)
Metarank is a tool that helps you easily build an advanced recommendation engine for your products or content on your website. To get started you only need historical performance data of your products (e.g. number of clicks) and additional metadata like product rating, genre, ingredients or price. In a YAML file, you define the features and the model parameters (e.g. number of iterations, modeling technique). The API service integrates with Apache Flink and can be easily integrated into Kubernetes clusters.
User Journey Analysis on your Website with Retentioneering (https://github.com/retentioneering/retentioneering-tools)
Retentioneering helps you to understand the user journey on your website. Retentioneering is a Python library that allows you to easily connect your Google Analytics data (in Bigquery). You define user-id, event-type and time stamp. From this data input a comprehensive graph network is created with gains and losses as you know it from a customer journey. In addition, customer segments are created that have a similar customer journey. This reduces the complexity of a purely descriptive view of the data.
Marketing Mix Modeling with Robyn (https://github.com/facebookexperimental/Robyn)
Less third-party cookie means less attribution models. The answer to this is Marketing Mix Modeling. Marketing mix models are regression models that use statistical probability to calculate the effect size of marketing channels and other independent variables. The advantage is that business context can be modeled much more realistically. For example, Google Searches for the own brand can be integrated to determine the share of the own brand strength in the revenue. Likewise, offline advertising measures can be modeled with other metrics in this context (e.g. offline advertising with GRPs). Robyn takes into account adstock effects, ROAS calculation and multicollinarity in the marketing channels. In addition, with simple functionality, budgets can be optimized using the predictions and results from marketing tests can be integrated into the model for calibration.
Contactless-Attendance-System
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Contactless Attendance System based on Face Recognition
Change the mail information in the Info.py.
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Contactless Attendance System
Install all the packages from requirements.txt.
What are some alternatives?
metarank - A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Face-Recognition-Cricket-Players - A Machine Learning Application to search the cricket players using the player's reference image and get the player's career stats data
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
CogAlg - This project is a Computer Vision implementation of general hierarchical pattern discovery principles introduced in README
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
EncrypC - 🔑 File Encryption Application using Python.
dbt-fal - do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.
python-hash - LiamLoads is a fast and secure 256-bit hashing function in pure Python.
sweetviz - Visualize and compare datasets, target values and associations, with one line of code.
Sudoku-Solver - 🎯 This Python-based Sudoku Solver utilizes the PyGame Library and Backtracking Algorithm to visualize and solve Sudoku puzzles efficiently. With its intuitive interface, users can input and interact with the Sudoku board, allowing for a seamless solving experience.
balder - Balder is a python test system that allows you to reuse a once written testcode for different but similar platforms/devices/applications.
greppo - Build & deploy geospatial applications quick and easy.