Increasingly large and diverse data sets allow us to form complex insights. With all this data, why would we limit ourselves by using data sampling instead? Sampling only works when it is put in the hands of data science specialists. In this article, learn about some of the downsides of using data sampling and how it limits and undermines business decisions. Read part one of the case against data sampling.
The full version of GPT-2 is now publicly available, following nearly nine months of heated debates and some smaller model releases. The large-scale unsupervised language model was kept under lock and key for this long as it was deemed too dangerous—a controversial decision that led to backlash from the open source community.
The early bird special for the Machine Learning Conference and the Voice Conference ends on November 7, 2019. This special offer includes a ticket discount of up to €210. Check out the conference programs, the tracks, speakers, and what to expect at these two conferences. A ticket for one includes admission to both!
The newest update for PyTorch-NLP is here. The 0.5.0 update adds support for Python 3.5, PyTorch 1.2, rewrites the README to help new users build an NLP pipeline, and adds some new features. See how PyTorch-NLP helps with natural language processing and how PyTorch compares to similar machine learning frameworks such as TensorFlow.
Google introduced TensorFlow Enterprise, a new collection of machine learning services and products. The beta version includes managed services, and some versions will receive long-term version support for up to three years. At the same time, Google unveiled the new website TensorBoard.dev.
We love open source! And now, two new recently open sourced pieces of software from Netflix have arrived. Mantis allows you to build realtime stream processing applications and Polynote is an IDE-inspired polyglot notebook. See what both of these can do, some of their use cases, and what important features set them apart.
Voice technologies are often caught between the user’s expectations of a truly personal assistant and the user’s desire for privacy and anonymity. We talked to Jeremy Wilken, moderator of the Design for Voice podcast and speaker at the upcoming VoiceCon Berlin, about a way to reconcile these expectations.
At the moment, big data is very popular and there is a wide variety of products available for handling data. In this article, read a case study about a German startup tackled their data problems and built a common data platform into their architecture. The data platform consists of four components: Ingestion, storage, process, and provisioning.
Artificial intelligence and machine learning are changing many industries, including e-commerce. This article examines some of the biggest trends in e-commerce that have appeared thanks to the growing use of AI technologies. Using these technologies can set your enterprise ahead of the competition and give you the edge you need.
Honey bee colony assessment is usually carried out via the laborious manual task of counting and classifying comb cells. Beekeepers perform this task many times throughout the year to asses the colony’s strength and to track its development. As you can imagine, this is an extremely time-consuming and error-prone task.
What lessons can Twitter and Facebook teach us about machine learning? These tech giants provide some ‘what to do’s, and even some ‘what not to do’s. Keep these important tips and practices in mind in order to improve your business model. Make sure you don’t forget about the end users’ experience and strive towards the best result.
At Machine Learning Conference 2019 in Munich, Christoph Henkelmann gave a talk about TensorFlow training on the JVM. We recorded the whole thing, and now you can watch it here (including slides) to learn all about how to combine a TensorFlow model with Java.
Reinforcement learning learns complex processes autonomously. No big data sets with the “right” answers are needed; the algorithms learn by experimenting. By using reinforcement learning, robots learn to walk, beat the world champion in Go, or fly a helicopter.
We are one step closer to TensorFlow 2.0.0. The new release candidate, 2.0.0-rc2 includes new features, improvements, breaking changes, and bug fixes. Catch up on what’s expected to arrive in TensorFlow 2.0. The next major release focuses on ease of use and simplicity, with plenty of updates and easy model building with Keras.