The first feature engine with time travel. Create and operate predictive models with event-based data.

Joined February 2018
81 Photos and videos
Kaskada (acquired by DataStax) retweeted
12 Apr 2023
Event processing and time-centric calculations are essential for businesses to leverage the power of real-time data for machine learning and other applications. Check out our blog and learn more lnkd.in/gKEEGrZV #AI #MachineLearning #realtimeai #Data
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Kaskada (acquired by DataStax) retweeted
17 Apr 2023
Unlock the power of Kaskada's query language! 🚀 Seamlessly navigate and manipulate data across different time points for efficient data analysis. lnkd.in/g93h3pPW #datatransformation #dataanalysis #ml #ai #data
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Kaskada (acquired by DataStax) retweeted
7 Apr 2023
Building real-time models can be challenging. @KaskadaOSS offers tools and technologies that simplify the process, making it easier and more efficient. lnkd.in/gUcyME9c #machinelearning #AI
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Kaskada (acquired by DataStax) retweeted
4 Apr 2023
Kaskada OSS single, high-level, declarative query language simplifies #DataEngineering and makes building data pipelines faster and more efficient. With Kaskada OSS, you can unlock insights from your data with ease. lnkd.in/gZhiQ7ez #MachineLearning #OpenSource
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Kaskada (acquired by DataStax) retweeted
31 Mar 2023
Kaskada OSS – an event-processing engine built on Rust and Apache Arrow. It features a high-level, declarative query language designed specifically for reasoning about events in bulk and in real time. Learn more: lnkd.in/gJvEve_N #OpenSource #DataEngineering
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Kaskada (acquired by DataStax) retweeted
29 Mar 2023
Looking for a powerful API for event processing? @KaskadaOSS empowers you to build scalable and efficient data pipelines with events - in bulk and real-time. Learn more lnkd.in/g93h3pPW #DataEngineering #MachineLearning #OpenSource”#DataScience"
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Excited to announce Kaskada has been acquired by @DataStax! Together, we’ll help businesses enable #realtimeAI, fueled with data from DataStax Astra DB. tinyurl.com/3kb74djx
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Data scientists spend 60% of their time cleaning data rather than collecting or analyzing important information. Learn how data quality can impact machine learning algorithms. Read more lnkd.in/g5zFkp4R #ml #machinelearning #datascientists #data #Algorithms

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Want to learn when should you use FOSS? Read our blog by Ryan Michael, VP of Engineering at Kaskada. lnkd.in/gSFdVwVj #opensource #data #dataandanalytics #MachineLearning

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Why you need a feature engine 1. Accelerate the feature engineering process and iterate quickly 2. Discover how different situations impact behavior and decisions 3. Deploy new features to production with a click of a button Learn more: lnkd.in/geniEe7S #engineering #ml
Behavioral ML models are challenging to develop and deploy using traditional compute engines. Try out Kaskada to instantly explore thousands more hypothesis and reduce time-to-production by 26x. lnkd.in/gT3bhBQK #ml #machinelearning #dataandanalytics #data #mlmodels
Model Context refers to the time domain used by a model to make predictions and therefore the relative time-slices that can be used to select training data for an ML model. Learn more here: lnkd.in/gCgug9Me #ml #data #machinelearning #dataandanalytics #DataScience

Kaskada - the only feature engine designed from the ground up for time-based feature engineering. It is built by data scientists for data scientists. Learn more at kaskada.com #datascientists #features #ml #machinelearning #data #dataandanalytics
Kaskada’s feature engineering language, FENL, makes defining and calculating features on event-based data simpler and more maintainable than the equivalents in the most common languages for building features on data, such as SQL and Python Pandas. #MachineLearning #DataScience
Do you want to learn how the Kaskada Feature Engine understands time? Read our blog by Brian Godsey, Data Science Lead at Kaskada, here: lnkd.in/gCv36WwM #data #datascience #ml #machinelearning #dataengineers #datacloud #dataandanalytics
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For real-time ML, choosing the appropriate model context to incorporate into your model’s training is a crucial element of your feature engineering process. Learn more at lnkd.in/gCgug9Me #dataanalytics #data #datascience #ml, #machinelearning #behavioralscience
Predicting customer behavior is not easy. Discover how different model contexts affect behavior. Read our blog: www.kaskada.comhttps://lnkd.in/gCgug9Me #bahavior #ml #machinelearning #data #DataAnalytics
Kaskada enables data scientists and engineers to make optimal decisions when choosing how to train their models. It ultimately leads to improved model performance and unmatched business growth. #growth #engineers #datascientists #ml #machinelearning #Data
Do you know that with Kaskada’s feature engine, you can better understand behavior and build high-quality features for machine learning models? Learn more kaskada.com #machinelearning #features #data #dataandanalytics #behavioralscience
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Would you like to learn how Kaskada’s feature engine adds to your existing data processing tools and understand how behavioral machine learning models can be built and deployed 26x faster? Watch our demo for data engineers lnkd.in/g2gyjFhu #ml #ai #data #DataEngineering