Based on our record, Scikit-learn should be more popular than rdkafka. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
We could have made some changes at the librdkafka level (see this), but we didn’t really want to pursue this (at least not yet). - Source: dev.to / over 1 year ago
As my first "real world" (ish) project in Vlang, I'm trying to copy https://github.com/confluentinc/confluent-kafka-go, which is a Go wrapper for Kafka C client library, https://github.com/edenhill/librdkafka. Source: over 1 year ago
If you're using Kafka in a Node.js app, it's likely that you'll need node-rdkafka. This is a library that wraps the librdkafka library and makes it available in Node.js. According to the project's README, "All the complexity of balancing writes across partitions and managing (possibly ever-changing) brokers should be encapsulated in the library.". - Source: dev.to / over 1 year ago
You are right, but in practice that's not what happens. Companies do not rely on open source libraries, the developers working for such companies do. I can give you a realistic example. If you want to use Kafka and Go, your probably only option is to use https://github.com/confluentinc/confluent-kafka-go. Its LICENSE explicitly says "no warranty". Now, what if I find a bug in the library? Only two realistic... - Source: Hacker News / over 1 year ago
Librdkafka – An Apache Kafka C/C++ client library\ (9 comments). Source: about 2 years ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Kafka Manager - A tool for managing Apache Kafka.
OpenCV - OpenCV is the world's biggest computer vision library
KafkaCenter - See what developers are saying about how they use KafkaCenter. Check out popular companies that use KafkaCenter and some tools that integrate with KafkaCenter.
NumPy - NumPy is the fundamental package for scientific computing with Python
KafkaHQ - Kafka GUI for Apache Kafka to manage topics, topics data, consumers group, schema registry, connect and more... - tchiotludo/kafkahq