Blog - Articles around AI, ML, DL and more
Tools for Deep Learning, importance of machine learning, Java and artificial intelligence - these and much more are topics our blog is dedicated to. We encounter new challenges every day and want to share our experience and insights with you. On this overview page you can see teasers of all previous blog posts. Feel free to click through, browse our current series of topics on MLOps and get excited about the posts to come! If you have any feedback, experiences, or topic requests, please feel free to contact us - we look forward to hearing from you.
- Amazon DJL - a new DL framework for Java
- BGL symposium 2019 - lecture 'AI and Magic'
- Deep Fakes - How to spot faked Images
- Deep Java Learning Introduction - Part 1: NDManager & NDArray
- DL4J Workshop at the ML Summit in Berlin
- Enterprise Tensorflow - Java vs. Python
- Enterprise TensorFlow 2 - Saving a trained model
- Enterprise TensorFlow 3 - Loading a SavedModel in Java
- Enterprise TensorFlow 4 - Executing a TensorFlow Session in Java
- Enterprise Tensorflow: Code Examples
- Git as a management tool for training data and experiments in ML
- Jax 2018 - Talks about DL4J and more
- Jax 2019 Recap
- ML Conference 2017 in Berlin
- MLOps: Establishment and operation of an AI
- Neural networks - The five most common mistakes
- NLP, NLU and NLG: AI and text
- Recap: ML Conference 2019 in Munich
- TensorFlow and Java - An interview with entwickler.de
- Types of Artificial Neural Networks
- Understanding AI - Part 1: What is AI?
- Understanding AI - Part 2: Symbolic AI, Neural Networks and Deep Learning
- Understanding AI - Part 3: Methods of symbolic AI
- Understanding AI - Part 4: The basics of Machine Learning
- Understanding AI - Part 5: Supervised & Unsupervised Learning in ML
- What are Neural Networks and how do they work?
Enterprise TensorFlow - Loading a SavedModel in Java
Part 3 in the series about Java / TensorFlow Interoperability, showing how to load a TensorFlow SavedModel in Java
Enterprise TensorFlow - Saving a trained model
Part 2 in the series about Java / TensorFlow Interoperability, discussing how to save a model so it can be reused in a different environment.
TensorFlow and Java - An interview with entwickler.de
Our CTO was interviewed about TensorFlow / Java Interoperability while at ML Conference 2017 in Berlin.
Enterprise Tensorflow: Code Examples
Overview over the example projects for TensorFlow / Java integration
Enterprise Tensorflow -Python vs. Java
This is the first part of a series of posts about Java and Tensorflow interop. It is a more extensive version of my talk at ML Conference 2017 in Berlin
ML Conference 2017 in Berlin
An announcement for my presentation at the ML Conference 2017 in Berlin