Kaskada (acquired by DataStax)

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

[Kaskada @KaskadaOSS]

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 https://t.co/jHCrZOIM1H
#AI #MachineLearning #realtimeai #Data

[Kaskada @KaskadaOSS]

Unlock the power of Kaskada's query language! 🚀 Seamlessly navigate and manipulate data across different time points for efficient data analysis. https://t.co/e5Dutqp4xq
#datatransformation #dataanalysis #ml #ai #data

[Kaskada @KaskadaOSS]

Building real-time models can be challenging. @KaskadaOSS offers tools and technologies that simplify the process, making it easier and more efficient. https://t.co/60y31JUWkv #machinelearning #AI

[Kaskada @KaskadaOSS]

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. https://t.co/EJvfPCJkgD #MachineLearning #OpenSource

[Kaskada @KaskadaOSS]

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: https://t.co/YWPWUsdpEd #OpenSource #DataEngineering

[Kaskada @KaskadaOSS]

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 https://t.co/e5DutqpCmY #DataEngineering #MachineLearning #OpenSource”#DataScience"

[Kaskada (acquired by DataStax) @KaskadaInc]

Excited to announce Kaskada has been acquired by @DataStax! Together, we’ll help businesses enable #realtimeAI, fueled with data from DataStax Astra DB.
https://t.co/DAukRpx38x

[Kaskada (acquired by DataStax) @KaskadaInc]

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 https://t.co/xKvDqpCAZk
#ml #machinelearning #datascientists #data #Algorithms

[Kaskada (acquired by DataStax) @KaskadaInc]

Want to learn when should you use FOSS? Read our blog by Ryan Michael, VP of Engineering at Kaskada. https://t.co/oB5lS34RAT
#opensource #data #dataandanalytics #MachineLearning

[Kaskada (acquired by DataStax) @KaskadaInc]

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: https://t.co/d9mGvfrn4O
#engineering #ml

[Kaskada (acquired by DataStax) @KaskadaInc]

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. https://t.co/SECEEQOaWt
#ml #machinelearning #dataandanalytics #data #mlmodels

[Kaskada (acquired by DataStax) @KaskadaInc]

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: https://t.co/bXAPUxxBxq
#ml #data #machinelearning #dataandanalytics #DataScience

[Kaskada (acquired by DataStax) @KaskadaInc]

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 https://t.co/Jwr4uFgpL6 #datascientists #features #ml #machinelearning #data #dataandanalytics

[Kaskada (acquired by DataStax) @KaskadaInc]

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

[Kaskada (acquired by DataStax) @KaskadaInc]

Do you want to learn how the Kaskada Feature Engine understands time? Read our blog by Brian Godsey, Data Science Lead at Kaskada, here: https://t.co/mAuBIaFHNR
#data #datascience #ml #machinelearning #dataengineers #datacloud #dataandanalytics

[Kaskada (acquired by DataStax) @KaskadaInc]

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 https://t.co/bXAPUxxBxq #dataanalytics #data #datascience #ml, #machinelearning #behavioralscience

[Kaskada (acquired by DataStax) @KaskadaInc]

Predicting customer behavior is not easy. Discover how different model contexts affect behavior. Read our blog: www.kaskada.comhttps://https://t.co/bXAPUxxBxq
#bahavior #ml #machinelearning #data #DataAnalytics

[Kaskada (acquired by DataStax) @KaskadaInc]

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

[Kaskada (acquired by DataStax) @KaskadaInc]

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 https://t.co/zuWSyYulgJ #machinelearning #features #data #dataandanalytics #behavioralscience

[Kaskada (acquired by DataStax) @KaskadaInc]

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
https://t.co/Gc7UqY3G0Q
#ml #ai #data #DataEngineering