Protractor

STEM is complex. We do tech recruiting differently so that you don't miss out on opportunities. We are STEM-educated, and former engineers and product managers.

[Protractor @protr_actor]

"The Great Tech Resignation" by Bloomberg
@Technology. Tech Talent: Take advantage of the musical chairs going on. #GreatResignation https://t.co/OgK6KNGerS

[Protractor @protr_actor]

What is your passion project? #GreatResignation https://t.co/2ccYgQon3w

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/PGTA633Md8

[Dataiku @dataiku]

Ubisoft was able to foster collaboration between business analysts and data scientists in order to upscale its analytics arm and generate more accurate predictions regarding user behavior and its marketplace. Read more about the odyssey of its data team: | https://t.co/sVGri4rjZN

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/Ou8H8bS5MM

[Databricks @databricks]

Koalas is an open-source project that provides a drop-in replacement for pandas.

In this technical blog post, learn how #PySpark users can leverage the native interaction between PySpark and Koalas to write code faster. https://t.co/p3Zi523QfN

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/rp2tf8aavc

[KNIME @knime]

Looking for a new read? Check out the list of #ebooks in the #KNIME Press series. These books will help you to use KNIME more successfully and efficiently! It also covers special use cases in the #CRM and #BI fields. Happy reading! 👀👓🛋️
https://t.co/9FWbSXEJaC
#datascience

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/f3plomeiD5

[Dataiku @dataiku]

9 Black Women that you should know in data science. | https://t.co/vcFzu7N36N #DataScience #DataQuality #DeepLearning #Algorithm #DataTeams #Automation #tech #MachineLearning

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/9p2y5ANIm3

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/5GeIImNVju

[Dataiku @dataiku]

Data In Quantum Machine Learning is a powerful. More on its quantum advantage: |
https://t.co/fLbfoEb123 #DataScience #Automation #MachineLearning #IoT #Business #ML #DataQuality #DeepLearning #bigdata #AI #Computing

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/o5RdJIttrQ

[Databricks @databricks]

Dive deeper into deploying modern IoT analytics. This blog details how to ingest real-time IIoT machine-to-machine data from field devices into Azure Data Lake Storage and perform complex time-series processing on Data Lake. https://t.co/M2BZC2Hgds

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/LCCq2NfL6e

[Databricks @databricks]

Dive deeper into deploying modern IoT analytics. In part 3 of this blog series, we'll look at how ML helps maximize the revenue of wind turbines using predictive maintenance that minimizes downtime — all with the help of Delta Lake. https://t.co/N7HpaNLieR

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/iF5n2aOorK

[Databricks @databricks]

Databricks Enterprise Cloud Service is now generally available.

#DataTeams can now innovate faster by conducting more experiments and running production workloads faster, more securely and with greater scalability. https://t.co/pyQ9L62pAT

#AWS

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/8fevk3teBX

[Databricks @databricks]

Something we hear from our customers is the challenges they have with the reliability, performance and flexibility of on-prem ETL pipelines.

So check out this story about how @createabond accelerated ETL pipelines from 18 hours to as little as 5 minutes. https://t.co/XexQlOZUWI

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/5ROY8ab2sn

[H2O.ai @h2oai]

Experts from @Discover, https://t.co/AHCQLzjMBA & BLDS came together to define #discrimination and #interpretability in the context of fair #lending and create a set of definitions of key #ML concepts. Download the ebook here: https://t.co/u93Mn1qf0d

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/wkKWfww2b4

[Dataiku @dataiku]

This team encouraged their machine-learning model to generate a hypothesis. What sort of actionable ideas flourished as a result? | https://t.co/3QlKcklvTJ #DataScience #Automation #MachineLearning #IoT #Business #ML #DataQuality #DeepLearning #AI

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/OQWat9CBMq

[Dataiku @dataiku]

There is ample opportunity for drug discovery and development with the help of AI and Machine Learning in each stage of the drug discovery process. Here’s a quantifiable argument for why you should be taking advantage of this technology: | https://t.co/6PcPGAlOrx #DataScience #AI

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/MhigCcifwV

[Databricks @databricks]

As content owners monetize their libraries through direct-to-consumer streaming services, their biggest challenge is reducing churn.

With the help of ML, learn how @Showtime revamped their production schedule to maximize customer lifetime value. https://t.co/VplrRYEqUL

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/TSCsJz9nqO

[Dataiku @dataiku]

The more data use cases the company takes on, the more difficult it is to maintain and reduce costs associated with the data-to-insights process. Here’s how you can reduce the total cost of ownership (TCO). | https://t.co/xPQ0RqHjJI #Dataiku #DataScience #ML #bigdata #AI

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/0N8JkCE9B2

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/BD8Jidy4aC

[KNIME @knime]

The 2nd edition of the “Will they blend?” #ebook is hot off the press and free to download. It contains 32 chapters describing #data blending for more than 50 data sources & external tools, from classic & new databases to cloud resources & more. https://t.co/vJp2ZAIg4g

#KNIME

[Protractor @protr_actor]

#DataScience #AI #MachineLearning #DeepLearning #Analytics https://t.co/FHcbcr5cex

[KNIME @knime]

With the latest release of #KNIME #Server 4.11, the capabilities of KNIME Executors have been extended. The new features include Executor Groups and Executor Reservation, AutoScaling on AWS, and Hybrid Installation. Read more at https://t.co/OjBXBVLDH9