Psyhackological/RGBfun

:rainbow: Flutter app for random color exploration. A playful way to explore color spaces & experiment with Flutter widgets.

Language: Dart - Size: 4.28 MB - Last synced at: 2 days ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

databricks-industry-solutions/segmentation

Create advanced customer segments to drive better purchasing predictions based on behaviors. Using sales data, campaigns and promotions systems, this solution helps derive a number of features that capture the behavior of various households. Build useful customer clusters to target with different promos and offers.

Language: Python - Size: 188 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 8 - Forks: 6

databricks-industry-solutions/item-onboarding

Item Onboarding Solution Accelerator

Language: Python - Size: 31.3 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

databricks-industry-solutions/personalized_image_gen

Use personalized images to enhance the output of an image generating model

Language: Python - Size: 57.9 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 4 - Forks: 4

databricks-industry-solutions/causal-incentive

Accelerator for customer incentive investment using causal inference techniques

Language: Jupyter Notebook - Size: 228 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 24 - Forks: 4

databricks-industry-solutions/product_copy_genai

Use generative AI to create product copy

Language: Python - Size: 88.9 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 1

databricks-industry-solutions/product-search

Semantic product search on Databricks

Language: Python - Size: 445 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 19 - Forks: 10

databricks-industry-solutions/customer-lifetime-value

Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases

Language: Python - Size: 134 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 13 - Forks: 5

databricks-industry-solutions/customer-er

Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence of each match

Language: Python - Size: 137 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 15 - Forks: 6

databricks-industry-solutions/safety-stock

Create fine-grained and viable estimates of buffer stock for raw material, work-in-progress or finished goods inventory items that can be scaled across the supply chain. Free up working capital that would be tied up in inventory and reallocate to more productive uses.

Language: Python - Size: 80.1 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

databricks-industry-solutions/rfm-segmentation

How an RFM segmentation can be performed and operationalized to enable personalized workflows

Language: Python - Size: 67.4 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

databricks-industry-solutions/wide-and-deep

Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.

Language: Python - Size: 89.8 KB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 1

databricks-industry-solutions/optimized-picking

Get started with our Solution Accelerator for Order Picking to apply optimization logic to each order to: Avoid unexpected delivery outcomes and assess the impact of small variations on order picking Minimize total store travel time to increase profitability

Language: Python - Size: 83 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

databricks-industry-solutions/computer-vision-foundations

Enabling Computer Vision Applications With the Data Lakehouse

Language: Python - Size: 95.7 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 2

databricks-industry-solutions/churn

Develop an understanding of how a customer lifetime should progress and examine where in that lifetime journey customers are likely to churn so you can effectively manage retention and reduce your churn rate.

Language: Python - Size: 142 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 1

databricks-industry-solutions/ab-testing 📦

Language: Python - Size: 114 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 2

databricks-industry-solutions/routing

Get started with our Solution Accelerator for Scalable Route Generation to optimize delivery routes and increase profitability

Language: Python - Size: 137 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 2

databricks-industry-solutions/multi-touch-attribution

Connect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.

Language: Python - Size: 87.9 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 4

databricks-industry-solutions/parts-demand-forecasting

Perform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Manage material shortages and predict overplanning

Language: Python - Size: 138 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 2

databricks-industry-solutions/pos-dlt

Get started with our Solution Accelerator to rapidly ingesting all data sources and types at scale, build highly scalable streaming data pipelines with Delta Live Tables to obtain a real-time view of operation, and leverage real-time insights to tackle your most pressing in-store information needs

Language: Python - Size: 111 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 4

databricks-industry-solutions/survival-analysis

Survival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.

Language: Python - Size: 73.2 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 3

databricks-industry-solutions/fuzzy-item-matching

Use machine learning and the Databricks Lakehouse Platform for product matching that can be used by marketplaces and suppliers for various purposes. Resolve differences between product definitions and descriptions and determine which items are likely pairs and which are distinct across disparate data sets.

Language: Python - Size: 61.5 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 3

databricks-industry-solutions/fine-grained-demand-forecasting

Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.

Language: R - Size: 145 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 6

databricks-industry-solutions/image-based-recommendations

Build a similarity-based image recommendation system for e-commerce that takes into account the visual similarity of items as an input for making product recommendations.

Language: Python - Size: 72.3 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 4

databricks-industry-solutions/survival

Preempt churn with the Databricks Solution Accelerator for predicting subscriber attrition. Learn how to analyze behavioral data to identify subscribers with an increased risk of cancellation. Then use machine learning to quantify the likelihood to churn as well as indicate which factors explain that risk.

Language: Python - Size: 83 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 4

databricks-industry-solutions/propensity

Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated

Language: Python - Size: 101 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 1

databricks-industry-solutions/on-shelf-availability

This Solution Accelerator shows how OOS can be solved with real-time data and analytics by using the Databricks Lakehouse Platform to solve on-shelf availability in real time to increase retail sales. The accelerator can also be used for supply chain solutions.

Language: Python - Size: 53.7 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 2

databricks-industry-solutions/market-basket-analysis

Increase conversion with personalized recommendations: Build a recommender that leverages product affinities to suggest additional items

Language: Python - Size: 71.3 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

databricks-industry-solutions/campaign-effectiveness

Identifying Campaign Effectiveness For Forecasting Foot Traffic

Language: Python - Size: 203 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 1