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Der Tag eines Data Scientist bei inovex – Mehr als nur Daten

2020-12-22T16:08:23+00:00

Der Tag eines Data Scientist kann vielfältig sein: Datenaufbereitung und -analyse, die Konzeption von KI-Modellen und viel mehr. Bei inovex sind die Möglichkeiten, sich einzubringen, nicht auf den eigenen Fachbereich beschränkt. Hier beschreibe ich, wie ein Tag als Senior Data Scientist bei inovex ablaufen kann.

Der Tag eines Data Scientist kann vielfältig sein: Datenaufbereitung und -analyse, die Konzeption von KI-Modellen und viel mehr. Bei inovex bleiben die Möglichkeiten,

Der Tag eines Data Scientist bei inovex – Mehr als nur Daten2020-12-22T16:08:23+00:00

A Close Look at the Workings of Apache Druid

2020-11-30T18:08:29+00:00

Apache Druid is a real-time analytics database that bridges the possibility of persisting large amounts of data with that of being able to extract information from it without having to wait unreasonable amounts of time. Read this article for operational insights and tips on how to get started.

Apache Druid is a real-time analytics database that bridges the possibility of persisting large amounts of data with that of being able to extract information from it

A Close Look at the Workings of Apache Druid2020-11-30T18:08:29+00:00

Modelling the Time-of-Arrival Using Distributions

2020-11-25T17:54:44+00:00

Estimating the time-of-arrival is a common Problem in many Scenarios. This post will show a Distribution-based approach that enables us to get more information about our time-of-arrival and how we could use this information for decision making in the logistics related industry.

Estimating the time-of-arrival is a common problem in a wide range of settings, e.g. in logistics. This post will show a distribution-based approach that enables us t

Modelling the Time-of-Arrival Using Distributions2020-11-25T17:54:44+00:00

Hybrid Methods for Time Series Forecasting

2020-10-19T10:59:52+00:00

Hybrid time series forecasting methods promise to advance time series forecasting by combining the best aspects of statistics and machine learning. This blog post gives a deeper understanding of the different approaches to forecasting and seeks to give hints on choosing an appropriate algorithm.

Time series forecasting is a crucial task in various fields of business and science. There are two co-existing approaches to time series forecasting, statistical meth

Hybrid Methods for Time Series Forecasting2020-10-19T10:59:52+00:00

Federated Learning: Frameworks for Decentralized Private Training – Part 2

2020-10-16T12:31:12+00:00

This blogpost evaluates three different Federated Learning frameworks and the concepts they use to achieve a collaborative training. With Federated Learning, numerous previously unusable sensitive data sources now can be used for collaborative Machine Learning.

This blog post evaluates three different Federated Learning frameworks and

Federated Learning: Frameworks for Decentralized Private Training – Part 22020-10-16T12:31:12+00:00

Systematic Collaborative Analyses of Experimental Data in a Federated Environment

2020-10-05T10:38:28+00:00

For a successful experimental, scientific research project, especially when handling vast amounts of data, many people need to be able to contribute at the same time. This makes a centrally accessibledata analysis platform inevitable.

For a successful scientific research project, especially when handling vast amounts of experimental data, many people need to be able to contribute at the same time.

Systematic Collaborative Analyses of Experimental Data in a Federated Environment2020-10-05T10:38:28+00:00

RecSys 2020: Highlights of a Special Conference

2020-09-29T01:13:53+00:00

Read my take on the highlights of the 14th ACM Conference on Recommender Systems, such as the winners of the best long and short paper awards as well as an assortment of the best workshops and tutorials.

The 14th ACM Conference on Recommender Systems was special in many ways: a fully virtual conference that did an amazing job to keep social interaction alive – e

RecSys 2020: Highlights of a Special Conference2020-09-29T01:13:53+00:00

A Case for Isolated Virtual Environments with PySpark

2020-09-16T15:00:21+00:00

This blogpost motivates the use of virtual environments with Python and then shows how they can be a handy tool when deploying PySpark jobs to managed clusters.

This blog post motivates the use of virtual environments with Python and then shows how they can be a handy tool when deploying PySpark jobs to managed clusters.

A Case for Isolated Virtual Environments with PySpark2020-09-16T15:00:21+00:00

Customer Journey verbessern mit Behavioral Economics & intelligenter Technologie: Eure Fragen beantwortet!

2020-09-08T14:12:15+00:00

Bei unserem Online Meetup zum Thema Customer Journey verbessern mit Behavioral Economics & intelligenter Technologie blieben einige Fragen unbeantwortet. Wir haben sie zusammengetragen und von den Vortragenden beantworten lassen.

Bei unserem Online Meetup zum Thema Customer Journey verbessern mit Behavioral Economics & intelligenter Technologie blieben einige Fragen unbeantwortet. Wir habe

Customer Journey verbessern mit Behavioral Economics & intelligenter Technologie: Eure Fragen beantwortet!2020-09-08T14:12:15+00:00

Federated Learning: A Guide to Collaborative Training with Decentralized Sensitive Data – Part 1

2020-10-12T15:59:59+00:00

This blog post explains how Federated Learning works and what privacy techniques are necessary to ensure that sensitive data is protected.

Nowadays, access to high-quality real-world data has a major impact on the success of data-driven projects, as the quality of a Machine Learning solution strongly dep

Federated Learning: A Guide to Collaborative Training with Decentralized Sensitive Data – Part 12020-10-12T15:59:59+00:00

Dive into Snorkel: Weak-Supervision on German Texts

2020-08-03T16:20:46+00:00

How do we proceed if we have almost no labeled data for a machine learning model? One answer may be: combining all the knowledge we have in one framework to get to the best of each world. This blogpost investigates the trending data programming framework Snorkel for the task of detecting bad language on German texts.

How do we proceed if we have almost no labeled data for a machine learning model? One answer may be: combining all the knowledge we have (labeled data, distant superv

Dive into Snorkel: Weak-Supervision on German Texts2020-08-03T16:20:46+00:00

Personalisierung mit Recommender Systems FAQ: Eure Fragen beantwortet

2020-07-27T12:27:35+00:00

Bei unserem Meetup zur Rolle von Recommender-Systemen im Omnichnannel-Marketing sind einige Fragen offen geblieben. Diese haben wir hier zusammengetragen und von unseren Expert:innen beantworten lassen.

Bei unserem Meetup zur Rolle von Recommender Systems im Omnichnannel-Marketing sind einige Fragen offen geblieben. Diese haben wir hier zusammengetragen und von unser

Personalisierung mit Recommender Systems FAQ: Eure Fragen beantwortet2020-07-27T12:27:35+00:00

Automated Feature Engineering with Open-Source Libraries

2020-07-20T16:56:10+00:00

In the hope of excellent features, without requiring domain experts spending days engineering them, lies this review of automated feature engineering with TPOT, auto-sklearn and autofeat.

In the hope of excellent features, without requiring domain experts spending days engineering them, lies this review of automated feature engineering with TPOT, auto-

Automated Feature Engineering with Open-Source Libraries2020-07-20T16:56:10+00:00

Causal Inference in Campaign Targeting

2020-05-13T16:18:46+00:00

In this article I will work through a synthetic example to show the efficacy of causal inference in marketing campaign targeting.

The following is one of two posts published alongside the JustCause framework, which we developed at inovex as a tool to foster good scientific practice in the field

Causal Inference in Campaign Targeting2020-05-13T16:18:46+00:00
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