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Based on our record, Scikit-learn should be more popular than rdkafka. It has been mentiond 31 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.
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 2 years 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 2 years 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 2 years 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 2 years ago
Librdkafka – An Apache Kafka C/C++ client library\ (9 comments). Source: about 3 years ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
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 / about 1 year 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 / almost 2 years ago
Kafka Manager - A tool for managing Apache Kafka.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
NSQ - A realtime distributed messaging platform.
OpenCV - OpenCV is the world's biggest computer vision library
KafkaHQ - Kafka GUI for Apache Kafka to manage topics, topics data, consumers group, schema registry, connect and more... - tchiotludo/kafkahq
NumPy - NumPy is the fundamental package for scientific computing with Python