How can we get use of Data Science in everyday like? What impact can it make for administration tasks? Is that possible to use Data Science in Fraud detection or Robotization?
activewizards.com/blog/top-7…
TensorFlow 2.1.0 was released a few days ago! The installation package now includes both the CPU and GPU versions, and it does not require a separate installation.
github.com/tensorflow/tensor…
Kafka is a popular open-source stream processing platform. Whether you are an expert in Kafka or don’t know anything about it, you can find something useful in this list of tutorials for yourself.
dzone.com/articles/kafka-clu…
Green or renewable energy is one of the main trends of the modern world, as well as machine learning. If you want to learn about implementations of machine learning in the field and the future of ML with green energy, check out this article.
altenergymag.com/article/201…
Deep-learning systems are truly amazing pieces of technology that emulates real humans better every year. This article focuses on a particular AI system that can mimic a human voice.
technologyreview.com/s/61364…
It may be challenging to manage a vast amount of information without special instruments. If we are talking about users, we have a lot of questions we want to answer.
dataform.co/blog/three-table…
Polynote is a new polyglot notebook in open-source space, used by the Netflix team. Taking into account the position of the cell during execution, IDE functionality, autocomplete the ability to write each cell in a different language.
medium.com/netflix-techblog/…
New release of OpenAI’s GPT-2 is out. To find out more about this world-famous text generation model and finding its creators, check this article.
openai.com/blog/gpt-2-1-5b-r…
Updates to TensorFlow are out! Now the topical version of TensorFlow is 2.1.0-rc0, and it supports Python 2. It also includes default support for CPU/GPU in one package using "pip install tensorflow."
github.com/tensorflow/tensor…
Today, many complex AI tasks are usually solved with the help of Deep Learning. But often there are problems and related questions that arise.
forbes.com/sites/forbestechc…
Majority of the recent deep learning algorithms rely heavily on hand-labeled data. And while a lot of them were successful, hand-labeling is not always the best solution, as it is rather costly. Find out more about this and alternatives.
ai.stanford.edu/blog/weak-su…
AI-powered hiring system brought new challenges into the hiring process for prospect employees of some of America’s most prominent employers.
washingtonpost.com/technolog…
Algorithm-based streaming services such as Spotify and TikTok are on the rise. Everything you see in your recommendations is derived either from your preferences or company policies.
theweek.com/articles/875017/…
Thomas Edison is one of the most controversial inventors of his generation. Despite all debates about his legacy and innovations' uniqueness, there is one fundamental invention. Let's talk about it -->
theatlantic.com/magazine/arc…
The data scientist is a vague profession. The area of responsibility and the range of tools data scientists use are very different among subjects and organizations. In the article, the author tries to create a taxonomy of data scientists.
hbr.org/2018/11/the-kinds-of…
Have you ever run a complex computational task? If so, you are probably aware of the constant convergence of cluster costs with service level agreements (SLAs). In terms of data and analytics, it is tough to cope with sudden surges in traffic.
cloud.google.com/blog/produc…
MongoDB and PostgreSQL are prevalent databases. But, don't confuse yourself, as they were created for different use cases. Here is an infographic that will help you to make the right decision.