20
Mar
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Infographic: Top 5 Python Libraries for Machine Learning
It is well-known in the Developer Scene that there is no better machine learning language than Python. One of the reasons why this programming language is so popular is the fact that it has a huge collection of great libraries, that makes the life of a developer a lot easier.
19
Feb
TensorFlow.js: What is possible with Machine learning in the browser?
When you talk about Machine Learning and Google's TensorFlow, most people think of Python and specialized hardware rather than JavaScript and any browser. This article explains what TensorFlow.js can do and why it makes sense to run machine learning in a browser.
8
Feb
Keynote http://commodity.ai
How can AI be turned into a commodity – a cheap, easily available product, that is used by everyone? Will it even be possible to turn AI into a commodity at all? Dr. Pieter Buteneers (Robovision) adresses these questions in this keynote from ML Conference 2018 in Berlin.
16
Nov
AI as a smart services for everyone
If you cannot or do not want to build an AI project from scratch, you have countless choices of ready-made services. But what can you do if the finished services do not fit the project? Customizable AI and ML models in the cloud, which you can train with your own data, provide a remedy.
12
Nov
Too many ideas, too little data – Overcome the cold start problem
The cold start problem affects both startups as well as established companies. Nonetheless, it also provides a great opportunity to collect new data with your customer’s problem in focus. How do you solve the cold start problem and arrive at a useful data pipeline? We talked to ML Conference speakers Markus Nutz and Thomas Pawlitzki about all this and more.
9
Nov
“Designing proper data collection today improves the quality of ML outcomes tomorrow”
Machine learning may have all sorts of use cases, but forecasting? In honor of the upcoming ML Conference, we talked to Philipp Beer about how data scientists can utilize ML in statistical forecasting. We talk about the advantages and disadvantages of modern vs. classical methods, how can one decide between the two, and where should they turn when they need good predictions for their business KPIs.
29
Oct
Coding deep learning: The absolute minimum an interested developer should know
Deep Learning is all the hype these days, beating another record most every week but writing code for deep learning is not just coding – it really helps if you have a basic understanding of what’s going on beneath. In this session from last year’s ML Conference, Sigrid Keydana offers a quick lesson on deep learning, as well as some tips and tricks for developers who’d like to dip their toes into this topic.
27
Sep
Man & Machines: The Dreamteam for your intelligent Marketing Strategy
Machine learning enables customized conversations between man and machine that can result in buying decisions. We asked Tina Nord and Kathleen Jaedtke to explain how this can be achieved through the use of dialogue-oriented technologies. Let’s take a look at how communication between man and machines works.
6
Jun
Find the outlier: Detecting sales fraud with machine learning
We spoke to data expert Canburak Tümer about how machine learning is being used to detect fraud in sales transactions. Find out how ML technology is helping to keep this tricky job under control and what it looks for when crunching the data.
15
May
Preparing Text Input for Machine Learning
ML Conference-Speaker Christoph Henkelmann says machine learning is basically nothing more than a numbers game. We’ve taken a closer look at what he means by that and and asked him to explain the principles of word processing from the point of view of a machine in more detail.